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      "contextWindow": 1047576,
      "description": "GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and GPT-4.5 across coding (54.6% SWE-bench Verified), instruction compliance (87.4% IFEval), and multimodal understanding benchmarks. It is tuned for precise code diffs, agent reliability, and high recall in large document contexts, making it ideal for agents, IDE tooling, and enterprise knowledge retrieval.",
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      "description": "Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination.",
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      "name": "Qwen-Plus",
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      "family": "glm",
      "id": "glm-4-6",
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      "description": "This latest 2.5 Flash model comes with improvements in two key areas we heard consistent feedback on:\n\nBetter agentic tool use: We've improved how the model uses tools, leading to better performance in more complex, agentic and multi-step applications. This model shows noticeable improvements on key agentic benchmarks, including a 5% gain on SWE-Bench Verified, compared to our last release (48.9% → 54%). More efficient: With thinking on, the model is now significantly more cost-efficient—achieving higher quality outputs while using fewer tokens, reducing latency and cost (see charts above).",
      "family": "gemini-flash",
      "id": "gemini-2-5-flash-preview-09-2025",
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      "maxOutputTokens": 65536,
      "name": "gemini-2.5-flash-preview-09-2025",
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      "family": "claude-opus",
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      "name": "claude-opus-4-1-20250805-thinking",
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      "ownedBy": "anthropic",
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      "description": "Qwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a \"thinking\" mode for complex reasoning, math, and code tasks, and a \"non-thinking\" mode for general conversational efficiency. The model demonstrates strong reasoning ability, multilingual support (100+ languages and dialects), advanced instruction-following, and agent tool-calling capabilities. It natively handles a 32K token context window and extends up to 131K tokens using YaRN-based scaling.",
      "family": "qwen",
      "id": "qwen3-a22b",
      "inputModalities": ["text"],
      "maxOutputTokens": 16384,
      "name": "Qwen3-235B-A22B",
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      "outputModalities": ["text"],
      "ownedBy": "alibaba",
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      "description": "MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom \"lightning attention\" mechanism, allowing it to process long sequences—up to 1 million tokens—while maintaining competitive FLOP efficiency. With 456 billion total parameters and 45.9B active per token, this variant is optimized for complex, multi-step reasoning tasks.\n\nTrained via a custom reinforcement learning pipeline (CISPO), M1 excels in long-context understanding, software engineering, agentic tool use, and mathematical reasoning. Benchmarks show strong performance across FullStackBench, SWE-bench, MATH, GPQA, and TAU-Bench, often outperforming other open models like DeepSeek R1 and Qwen3-235B.",
      "family": "minimax",
      "id": "minimax-m1",
      "inputModalities": ["text"],
      "maxOutputTokens": 128000,
      "name": "MiniMax-M1",
      "openWeights": false,
      "outputModalities": ["text"],
      "ownedBy": "minimax",
      "pricing": {
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          "perMillionTokens": 0.132
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        "output": {
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      "family": "deepseek-thinking",
      "id": "deepseek-reasoner",
      "inputModalities": ["text"],
      "maxOutputTokens": 384000,
      "name": "Deepseek-Reasoner",
      "openWeights": true,
      "outputModalities": ["text"],
      "ownedBy": "deepseek",
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      "family": "qwen",
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      "maxOutputTokens": 8192,
      "name": "Qwen-Max-Latest",
      "openWeights": false,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
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          "perMillionTokens": 0.343
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          "perMillionTokens": 1.372
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    {
      "capabilities": ["function-call"],
      "contextWindow": 262144,
      "description": "The code generation model based on Qwen3 has powerful Coding Agent capabilities, achieving state-of-the-art performance compared to open-source models.The model adopts tiered pricing.",
      "family": "qwen",
      "id": "qwen3-coder-a35b-instruct",
      "inputModalities": ["text"],
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      "name": "qwen3-coder-480b-a35b-instruct",
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      "ownedBy": "alibaba",
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      "description": "Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks. Its unique ability to switch seamlessly between a thinking mode for complex reasoning and a non-thinking mode for efficient dialogue ensures versatile, high-quality performance.\n\nSignificantly outperforming prior models like QwQ and Qwen2.5, Qwen3 delivers superior mathematics, coding, commonsense reasoning, creative writing, and interactive dialogue capabilities. The Qwen3-30B-A3B variant includes 30.5 billion parameters (3.3 billion activated), 48 layers, 128 experts (8 activated per task), and supports up to 131K token contexts with YaRN, setting a new standard among open-source models.",
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      "family": "minimax",
      "id": "minimax-m2-1",
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      "name": "MiniMax-M2.1",
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      "description": "Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance across common benchmarks compared to earlier Flash models. By default, \"thinking\" (i.e. multi-pass reasoning) is disabled to prioritize speed, but developers can enable it via the [Reasoning API parameter](https://openrouter.ai/docs/use-cases/reasoning-tokens) to selectively trade off cost for intelligence. ",
      "family": "gemini-flash-lite",
      "id": "gemini-2-5-flash-lite-preview-09-2025",
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    },
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      "description": "Grok 4.1 is a new conversational model with significant improvements in real-world usability, delivering exceptional performance in creative, emotional, and collaborative interactions. It is more perceptive to nuanced user intent, more engaging to converse with, and more coherent in personality, while fully preserving its core intelligence and reliability. Built on large-scale reinforcement learning infrastructure, the model is optimized for style, personality, helpfulness, and alignment, and leverages frontier agentic reasoning models as reward evaluators to autonomously assess and iterate on responses at scale, significantly enhancing overall interaction quality.",
      "family": "grok",
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      "description": "GPT-5 Pro is OpenAI’s most advanced model, offering major improvements in reasoning, code quality, and user experience. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and accuracy in high-stakes use cases. It supports test-time routing features and advanced prompt understanding, including user-specified intent like \"think hard about this.\" Improvements include reductions in hallucination, sycophancy, and better performance in coding, writing, and health-related tasks.",
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      "description": "GPT-5.1 Chat refers to the GPT-5.1 snapshot currently used in ChatGPT and is optimized for conversational use cases. While GPT-5.1 is recommended for most API applications, GPT-5.1 Chat is ideal for testing the latest improvements in chat-based interactions.",
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      "name": "gpt-5.1-chat-latest",
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      "contextWindow": 128000,
      "description": "GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K tokens, processes complex page layouts and charts directly as visual inputs, and integrates native multimodal function calling to connect perception with downstream tool execution. The model also enables interleaved image-text generation and UI reconstruction workflows, including screenshot-to-HTML synthesis and iterative visual editing.",
      "family": "glm",
      "id": "glm-4-6v",
      "inputModalities": ["image", "text", "video"],
      "maxOutputTokens": 32768,
      "name": "GLM-4.6V",
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      "ownedBy": "zhipu",
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      },
      "reasoning": {
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      }
    },
    {
      "alias": ["claude-haiku-4-5"],
      "capabilities": ["function-call", "reasoning", "image-recognition", "file-input", "web-search", "computer-use"],
      "contextWindow": 200000,
      "family": "claude-haiku",
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          "currency": "USD",
          "perMillionTokens": 0.035
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      "reasoning": {
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        "thinkingTokenLimits": {
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    },
    {
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        "function-call",
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        "audio-recognition",
        "audio-generation",
        "video-recognition"
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      "contextWindow": 32768,
      "family": "qwen",
      "id": "qwen-omni-turbo",
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      "maxOutputTokens": 2048,
      "name": "Qwen-Omni Turbo",
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      "outputModalities": ["text", "audio"],
      "ownedBy": "alibaba",
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          "currency": "USD",
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        "output": {
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    {
      "capabilities": ["function-call", "image-recognition"],
      "contextWindow": 131072,
      "description": "Qwen VL Max is a visual understanding model with 7500 tokens context length. It excels in delivering optimal performance for a broader spectrum of complex tasks.\n",
      "family": "qwen",
      "id": "qwen-vl-max",
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      "maxOutputTokens": 8192,
      "name": "Qwen-VL Max",
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      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.8
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        "output": {
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          "perMillionTokens": 3.2
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    {
      "capabilities": ["function-call"],
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      "description": "Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual use, while remaining robust on alignment and formatting. Compared with prior Qwen3 instruct variants, it focuses on higher throughput and stability on ultra-long inputs and multi-turn dialogues, making it well-suited for RAG, tool use, and agentic workflows that require consistent final answers rather than visible chain-of-thought.\n\nThe model employs scaling-efficient training and decoding to improve parameter efficiency and inference speed, and has been validated on a broad set of public benchmarks where it reaches or approaches larger Qwen3 systems in several categories while outperforming earlier mid-sized baselines. It is best used as a general assistant, code helper, and long-context task solver in production settings where deterministic, instruction-following outputs are preferred.",
      "family": "qwen",
      "id": "qwen3-next-a3b-instruct",
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      "maxOutputTokens": 32768,
      "name": "Qwen3-Next 80B-A3B Instruct",
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      "ownedBy": "alibaba",
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          "perMillionTokens": 2
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        "supportedEfforts": ["none"]
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      "capabilities": ["reasoning", "function-call"],
      "contextWindow": 1000000,
      "description": "Qwen-Turbo, based on Qwen2.5, is a 1M context model that provides fast speed and low cost, suitable for simple tasks.",
      "family": "qwen",
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      "maxOutputTokens": 16384,
      "name": "Qwen Turbo",
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      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "cacheRead": {
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    {
      "capabilities": ["function-call", "reasoning", "image-recognition", "file-input"],
      "contextWindow": 131072,
      "description": "The Qwen3 series open-source models include hybrid models, thinking models, and non-thinking models, with both reasoning capabilities and general abilities reaching industry SOTA levels at the same scale.",
      "family": "qwen",
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      "inputModalities": ["text", "image"],
      "maxOutputTokens": 32768,
      "name": "Qwen3-VL 235B-A22B",
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      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.7
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        "output": {
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    {
      "capabilities": ["function-call"],
      "contextWindow": 1000000,
      "description": "Qwen3 Coder Flash is Alibaba's fast and cost efficient version of their proprietary Qwen3 Coder Plus. It is a powerful coding agent model specializing in autonomous programming via tool calling and environment interaction, combining coding proficiency with versatile general-purpose abilities.",
      "family": "qwen",
      "id": "qwen3-coder-flash",
      "inputModalities": ["text"],
      "maxOutputTokens": 65536,
      "name": "Qwen3 Coder Flash",
      "openWeights": false,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
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        "input": {
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          "perMillionTokens": 0.3
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        "output": {
          "currency": "USD",
          "perMillionTokens": 1.5
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      "reasoning": {
        "supportedEfforts": ["none"]
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    },
    {
      "capabilities": [
        "function-call",
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        "image-recognition",
        "file-input",
        "video-recognition"
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      "contextWindow": 131072,
      "description": "The Qwen3-VL series’ second-largest MoE model Thinking version offers fast response speed, stronger multimodal understanding and reasoning, visual agent capabilities, and ultra-long context support for long videos and long documents; it features comprehensive upgrades in image/video understanding, spatial perception, and universal recognition abilities, making it capable of handling complex real-world tasks.",
      "family": "qwen",
      "id": "qwen3-vl-a3b",
      "inputModalities": ["text", "image"],
      "maxOutputTokens": 32768,
      "name": "Qwen3-VL 30B-A3B",
      "openWeights": true,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.2
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        "output": {
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      "reasoning": {
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    },
    {
      "capabilities": ["function-call", "reasoning"],
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      "description": "Qwen3-4B is a 4 billion parameter dense language model from the Qwen3 series, designed to support both general-purpose and reasoning-intensive tasks. It introduces a dual-mode architecture—thinking and non-thinking—allowing dynamic switching between high-precision logical reasoning and efficient dialogue generation. This makes it well-suited for multi-turn chat, instruction following, and complex agent workflows.",
      "family": "qwen",
      "id": "qwen3",
      "inputModalities": ["text"],
      "maxOutputTokens": 16384,
      "name": "Qwen3 14B",
      "openWeights": true,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
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        "cacheRead": {
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        "input": {
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        "output": {
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      "reasoning": {
        "supportedEfforts": ["none", "auto"]
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    },
    {
      "capabilities": ["reasoning", "function-call", "image-recognition"],
      "contextWindow": 131072,
      "family": "qvq",
      "id": "qvq-max",
      "inputModalities": ["text", "image"],
      "maxOutputTokens": 8192,
      "name": "QVQ Max",
      "openWeights": false,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
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        "output": {
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    {
      "capabilities": ["function-call", "reasoning", "image-recognition", "file-input", "video-recognition"],
      "contextWindow": 262144,
      "description": "The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers state-of-the-art performance comparable to leading-edge models across a wide range of tasks, including language understanding, logical reasoning, code generation, agent-based tasks, image understanding, video understanding, and graphical user interface (GUI) interactions. With its robust code-generation and agent capabilities, the model exhibits strong generalization across diverse agent.",
      "family": "qwen",
      "id": "qwen3-5-a17b",
      "inputModalities": ["audio", "image", "text", "video"],
      "maxOutputTokens": 65536,
      "name": "Qwen3.5 397B-A17B",
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      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
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        "input": {
          "currency": "USD",
          "perMillionTokens": 0.6
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        "output": {
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      },
      "reasoning": {
        "supportedEfforts": ["none", "low", "medium", "high"],
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      }
    },
    {
      "capabilities": ["function-call", "reasoning"],
      "contextWindow": 8192,
      "family": "qwen",
      "id": "qwen-plus-character-ja",
      "inputModalities": ["text"],
      "maxOutputTokens": 512,
      "name": "Qwen Plus Character (Japanese)",
      "openWeights": false,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.5
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 1.4
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      },
      "reasoning": {
        "supportedEfforts": ["none", "low", "medium", "high"],
        "thinkingTokenLimits": {
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      }
    },
    {
      "capabilities": ["function-call", "structured-output"],
      "contextWindow": 131072,
      "family": "qwen",
      "id": "qwen2-5-instruct",
      "inputModalities": ["text"],
      "maxOutputTokens": 8192,
      "name": "Qwen2.5 14B Instruct",
      "openWeights": true,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
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        "output": {
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      "reasoning": {
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    {
      "capabilities": ["reasoning", "function-call"],
      "contextWindow": 131072,
      "family": "qwen",
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      "maxOutputTokens": 8192,
      "name": "QwQ Plus",
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      "outputModalities": ["text"],
      "ownedBy": "alibaba",
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        "input": {
          "currency": "USD",
          "perMillionTokens": 0.8
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        "output": {
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    },
    {
      "capabilities": ["function-call"],
      "contextWindow": 262144,
      "description": "Qwen3-Coder-30B-A3B-Instruct is a 30.5B parameter Mixture-of-Experts (MoE) model with 128 experts (8 active per forward pass), designed for advanced code generation, repository-scale understanding, and agentic tool use. Built on the Qwen3 architecture, it supports a native context length of 256K tokens (extendable to 1M with Yarn) and performs strongly in tasks involving function calls, browser use, and structured code completion.\n\nThis model is optimized for instruction-following without “thinking mode”, and integrates well with OpenAI-compatible tool-use formats. ",
      "family": "qwen",
      "id": "qwen3-coder-a3b-instruct",
      "inputModalities": ["text"],
      "maxOutputTokens": 65536,
      "name": "Qwen3-Coder 30B-A3B Instruct",
      "openWeights": true,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
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        },
        "input": {
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        "output": {
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      },
      "reasoning": {
        "supportedEfforts": ["none"]
      }
    },
    {
      "capabilities": ["image-recognition", "function-call", "file-input"],
      "contextWindow": 34096,
      "family": "qwen",
      "id": "qwen-vl-ocr",
      "inputModalities": ["text", "image"],
      "maxOutputTokens": 4096,
      "name": "Qwen-VL OCR",
      "openWeights": false,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.72
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        "output": {
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      }
    },
    {
      "capabilities": [
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        "image-recognition",
        "audio-recognition",
        "audio-generation",
        "video-recognition"
      ],
      "contextWindow": 65536,
      "family": "qwen",
      "id": "qwen3-omni-flash",
      "inputModalities": ["text", "image", "audio", "video"],
      "maxOutputTokens": 16384,
      "name": "Qwen3-Omni Flash",
      "openWeights": false,
      "outputModalities": ["text", "audio"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.43
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        "output": {
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          "perMillionTokens": 1.66
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      },
      "reasoning": {
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    },
    {
      "capabilities": [
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        "audio-generation",
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      "family": "qwen",
      "id": "qwen3-omni-flash-realtime",
      "inputModalities": ["text", "image", "audio", "video"],
      "maxOutputTokens": 16384,
      "name": "Qwen3-Omni Flash Realtime",
      "openWeights": false,
      "outputModalities": ["text", "audio"],
      "ownedBy": "alibaba",
      "pricing": {
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        "output": {
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      },
      "reasoning": {
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    },
    {
      "capabilities": ["function-call", "image-recognition", "file-input", "video-recognition"],
      "contextWindow": 131072,
      "description": "Qwen2.5-VL-32B is a multimodal vision-language model fine-tuned through reinforcement learning for enhanced mathematical reasoning, structured outputs, and visual problem-solving capabilities. It excels at visual analysis tasks, including object recognition, textual interpretation within images, and precise event localization in extended videos. Qwen2.5-VL-32B demonstrates state-of-the-art performance across multimodal benchmarks such as MMMU, MathVista, and VideoMME, while maintaining strong reasoning and clarity in text-based tasks like MMLU, mathematical problem-solving, and code generation.",
      "family": "qwen",
      "id": "qwen2-5-vl-instruct",
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      "maxOutputTokens": 8192,
      "name": "Qwen2.5-VL 72B Instruct",
      "openWeights": true,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
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      },
      "reasoning": {
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    },
    {
      "capabilities": ["reasoning", "function-call", "image-recognition"],
      "contextWindow": 262144,
      "description": "The Qwen3 series visual understanding model achieves an effective fusion of thinking and non-thinking modes. Its visual agent capabilities reach world-class levels on public test sets such as OS World. This version features comprehensive upgrades in visual coding, spatial perception, and multimodal reasoning; visual perception and recognition abilities are greatly enhanced, supporting ultra-long video understanding.",
      "family": "qwen",
      "id": "qwen3-vl-plus",
      "inputModalities": ["text", "image"],
      "maxOutputTokens": 32768,
      "name": "Qwen3-VL Plus",
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      "outputModalities": ["text"],
      "ownedBy": "alibaba",
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      },
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    },
    {
      "capabilities": [
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        "audio-recognition",
        "audio-generation",
        "video-recognition"
      ],
      "contextWindow": 32768,
      "family": "qwen",
      "id": "qwen2-5-omni",
      "inputModalities": ["text", "image", "audio", "video"],
      "maxOutputTokens": 2048,
      "name": "Qwen2.5-Omni 7B",
      "openWeights": true,
      "outputModalities": ["text", "audio"],
      "ownedBy": "alibaba",
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      }
    },
    {
      "capabilities": ["function-call"],
      "contextWindow": 32768,
      "description": "Qwen-Max, based on Qwen2.5, provides the best inference performance among [Qwen models](/qwen), especially for complex multi-step tasks. It's a large-scale MoE model that has been pretrained on over 20 trillion tokens and further post-trained with curated Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) methodologies. The parameter count is unknown.",
      "family": "qwen",
      "id": "qwen-max",
      "inputModalities": ["text"],
      "maxOutputTokens": 8192,
      "name": "Qwen Max",
      "openWeights": false,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.32
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 1.6
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        "output": {
          "currency": "USD",
          "perMillionTokens": 6.4
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      }
    },
    {
      "capabilities": ["function-call", "image-recognition", "audio-recognition", "audio-generation"],
      "contextWindow": 32768,
      "family": "qwen",
      "id": "qwen-omni-turbo-realtime",
      "inputModalities": ["text", "image", "audio"],
      "maxOutputTokens": 2048,
      "name": "Qwen-Omni Turbo Realtime",
      "openWeights": false,
      "outputModalities": ["text", "audio"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
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      }
    },
    {
      "contextWindow": 16384,
      "description": "Based on the comprehensive upgrade of Qwen3, this flagship translation large model supports bidirectional translation across 92 languages. It offers fully enhanced model performance and translation quality, along with more stable terminology customization, format fidelity, and domain-prompting capabilities, making translations more accurate and natural.",
      "family": "qwen",
      "id": "qwen-mt-turbo",
      "inputModalities": ["text"],
      "maxOutputTokens": 8192,
      "name": "Qwen-MT Turbo",
      "openWeights": false,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.16
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        "output": {
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      }
    },
    {
      "contextWindow": 16384,
      "description": "Based on the comprehensive upgrade of Qwen3, this flagship translation large model supports bidirectional translation across 92 languages. It offers fully enhanced model performance and translation quality, along with more stable terminology customization, format fidelity, and domain-prompting capabilities, making translations more accurate and natural.",
      "family": "qwen",
      "id": "qwen-mt-plus",
      "inputModalities": ["text"],
      "maxOutputTokens": 8192,
      "name": "Qwen-MT Plus",
      "openWeights": false,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
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          "perMillionTokens": 2.46
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      "reasoning": {
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    },
    {
      "capabilities": ["function-call"],
      "contextWindow": 262144,
      "description": "Qwen3-Max is an updated release built on the Qwen3 series, offering major improvements in reasoning, instruction following, multilingual support, and long-tail knowledge coverage compared to the January 2025 version. It delivers higher accuracy in math, coding, logic, and science tasks, follows complex instructions in Chinese and English more reliably, reduces hallucinations, and produces higher-quality responses for open-ended Q&A, writing, and conversation. The model supports over 100 languages with stronger translation and commonsense reasoning, and is optimized for retrieval-augmented generation (RAG) and tool calling, though it does not include a dedicated “thinking” mode.",
      "family": "qwen",
      "id": "qwen3-max",
      "inputModalities": ["text"],
      "maxOutputTokens": 65536,
      "name": "Qwen3 Max",
      "openWeights": false,
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
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        "input": {
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      },
      "reasoning": {
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      "description": "May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass.\n\nFully open-source model.",
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      "id": "command-r-08-2024",
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      "name": "Command R",
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      "family": "command-r",
      "id": "command-r-plus-08-2024",
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      "id": "c4ai-aya-vision",
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      "name": "Aya Vision 32B",
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      "outputModalities": ["text"],
      "ownedBy": "cohere"
    },
    {
      "capabilities": ["function-call"],
      "contextWindow": 128000,
      "description": "Command R7B (12-2024) is a small, fast update of the Command R+ model, delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning and multiple steps.\n\nUse of this model is subject to Cohere's [Usage Policy](https://docs.cohere.com/docs/usage-policy) and [SaaS Agreement](https://cohere.com/saas-agreement).",
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      "description": "Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance across common benchmarks compared to earlier Flash models. By default, \"thinking\" (i.e. multi-pass reasoning) is disabled to prioritize speed, but developers can enable it via the [Reasoning API parameter](https://openrouter.ai/docs/use-cases/reasoning-tokens) to selectively trade off cost for intelligence. ",
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      "maxOutputTokens": 28000,
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      "inputModalities": ["text", "image"],
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      "name": "Qianfan Ocr Fast",
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      "description": "The newly upgraded Tongyi Wanxiang 2.2 text-to-video offers higher video quality. It optimizes video generation stability and success rate, features stronger instruction-following capabilities, consistently maintains image text, portrait, and product consistency, and provides precise camera motion control.",
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      "name": "Wan2 5 I2v Preview",
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      "inputModalities": ["text"],
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      "name": "Deepseek V3 1 Fast",
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      "description": "Veo 2.0 is an advanced video generation model capable of producing high-quality videos based on text or image prompts. It excels in understanding real-world physics and human motion, resulting in fluid character movements and lifelike scenes. Veo 2.0 supports various visual styles and camera control options, including lens types, angles, and motion effects. Users can generate 8-second video clips at 720p resolution.",
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      "inputModalities": ["video"],
      "name": "Veo 2 0 Generate 001",
      "outputModalities": ["video"],
      "ownedBy": "google",
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      "description": "veo3.1 reverse model, and other available model names that can be requested include: veo3.1-pro and veo3.1-components. The price is currently tentatively set to be calculated per token, approximately $0.05 per request.",
      "id": "veo3-1",
      "inputModalities": ["text"],
      "name": "Veo3 1",
      "outputModalities": ["video"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 200
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 200
        }
      }
    },
    {
      "capabilities": ["image-generation"],
      "description": "Imagen 4 is a high-quality text-to-image model developed by Google, designed for strong visual fidelity, diverse artistic styles, and precise controllability. It delivers near photographic realism with sharp details and natural lighting while significantly reducing common artifacts such as distorted hands. The model supports a wide range of styles including photorealistic, illustration, anime, oil painting, and pixel art, and offers flexible aspect ratios for use cases from content covers to mobile wallpapers. It also enables image editing and secondary creation on existing images, provides fast and stable generation, and offers strong commercial usability with high visual quality and reliable content safety.",
      "id": "imagen-4-0",
      "imageGeneration": {
        "modes": {
          "generate": {
            "supports": {
              "aspectRatio": {
                "default": "ASPECT_1_1",
                "options": ["ASPECT_1_1", "ASPECT_3_4", "ASPECT_4_3", "ASPECT_9_16", "ASPECT_16_9"],
                "render": "chips",
                "type": "enum"
              },
              "numImages": {
                "default": 1,
                "max": 4,
                "min": 1,
                "type": "range"
              },
              "personGeneration": {
                "options": ["DONT_ALLOW", "ALLOW_ADULT", "ALLOW_ALL"],
                "type": "enum"
              }
            }
          }
        }
      },
      "inputModalities": ["text", "image"],
      "name": "Imagen 4 0",
      "outputModalities": ["image"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
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        }
      }
    },
    {
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      "id": "imagen-4-0-fast-generate-preview-06-06",
      "imageGeneration": {
        "modes": {
          "generate": {
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                "default": "ASPECT_1_1",
                "options": ["ASPECT_1_1", "ASPECT_3_4", "ASPECT_4_3", "ASPECT_9_16", "ASPECT_16_9"],
                "render": "chips",
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              "numImages": {
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              "personGeneration": {
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                "type": "enum"
              }
            }
          }
        }
      },
      "inputModalities": ["text", "image"],
      "name": "Imagen 4 0 Fast Generate Preview 06 06",
      "outputModalities": ["image"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      }
    },
    {
      "capabilities": ["image-generation"],
      "id": "imagen-4-0-ultra",
      "imageGeneration": {
        "modes": {
          "generate": {
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                "options": ["ASPECT_1_1", "ASPECT_3_4", "ASPECT_4_3", "ASPECT_9_16", "ASPECT_16_9"],
                "render": "chips",
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                "type": "enum"
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            }
          }
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      },
      "inputModalities": ["text", "image"],
      "name": "Imagen 4 0 Ultra",
      "outputModalities": ["image"],
      "ownedBy": "google",
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        "input": {
          "currency": "USD",
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        },
        "output": {
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          "perMillionTokens": 2
        }
      }
    },
    {
      "description": "PP-StructureV3 is an efficient and comprehensive document parsing solution that can effectively convert document images and PDF files into structured content (such as Markdown format). It features powerful capabilities including layout area detection, table recognition, formula recognition, chart understanding, and multi-column reading order recovery. This tool performs excellently across various document types and can handle complex document data.",
      "id": "pp-structurev3",
      "inputModalities": ["text"],
      "name": "Pp Structurev3",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0
        }
      }
    },
    {
      "capabilities": ["video-generation"],
      "description": "Veo 3.0 Generate Preview is an advanced AI video generation model that supports text-to-video creation with synchronized audio, featuring excellent physical simulation and lip-sync capabilities. Users can generate vivid video clips from short story prompts. 🎟️ Limited-Time Deal: Save 10% Now.",
      "id": "veo-3-0-generate-preview",
      "inputModalities": ["text", "image", "video"],
      "name": "Veo 3 0 Generate Preview",
      "outputModalities": ["video"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      }
    },
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      "description": "Veo 3.1 is Google's state-of-the-art model for generating high-fidelity, 8-second 720p , 1080p or 4k videos featuring stunning realism and natively generated audio.",
      "id": "veo-3-1-fast-generate-preview",
      "inputModalities": ["text", "image", "video"],
      "name": "Veo 3 1 Fast Generate Preview",
      "outputModalities": ["video"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0
        }
      }
    },
    {
      "capabilities": ["video-generation"],
      "description": "Veo 3.1 is Google's state-of-the-art model for generating high-fidelity, 8-second 720p , 1080p or 4k videos featuring stunning realism and natively generated audio.",
      "id": "veo-3-1-generate-preview",
      "inputModalities": ["text", "image", "video"],
      "name": "Veo 3 1 Generate Preview",
      "outputModalities": ["video"],
      "ownedBy": "google",
      "pricing": {
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          "perMillionTokens": 2
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        "output": {
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        }
      }
    },
    {
      "capabilities": ["reasoning"],
      "contextWindow": 119000,
      "description": "ERNIE 5.0 is the next-generation natively multimodal foundation model in the ERNIE family. Built on a unified multimodal architecture, it jointly learns from text, images, audio, and video to deliver broad multimodal capabilities.\n\nERNIE 5.0 features significantly upgraded core capabilities and shows strong performance across benchmarks, with notable gains in multimodal understanding, instruction following, creative writing, factual accuracy, and agent planning with tool use.",
      "id": "ernie-5-0-thinking-exp",
      "inputModalities": ["text", "image"],
      "maxOutputTokens": 64000,
      "name": "Ernie 5 0 Thinking Exp",
      "outputModalities": ["text"],
      "ownedBy": "baidu",
      "pricing": {
        "cacheRead": {
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          "perMillionTokens": 0.82192
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.82192
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        "output": {
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          "perMillionTokens": 3.28768
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      }
    },
    {
      "capabilities": ["reasoning"],
      "contextWindow": 131072,
      "description": "Switchpoint AI's router instantly analyzes your request and directs it to the optimal AI from an ever-evolving library. \n\nAs the world of LLMs advances, our router gets smarter, ensuring you always benefit from the industry's newest models without changing your workflow.\n\nThis model is configured for a simple, flat rate per response here on OpenRouter. It's powered by the full routing engine from [Switchpoint AI](https://www.switchpoint.dev).",
      "id": "router",
      "inputModalities": ["text"],
      "name": "Switchpoint Router",
      "outputModalities": ["text"],
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.1
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.85
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 3.4
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      }
    },
    {
      "capabilities": ["reasoning", "function-call", "structured-output", "image-recognition", "web-search"],
      "description": "Supports high concurrency.  \nThe Gemini 2.5 Pro preview version is here, with higher limits for production testing.  \nGoogle's latest and most powerful model;",
      "id": "gemini-2-5-pro-preview-03-25",
      "inputModalities": ["text", "image"],
      "name": "Gemini 2 5 Pro Preview 03 25",
      "outputModalities": ["text"],
      "ownedBy": "google",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.125
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 1.25
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 10
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      },
      "reasoning": {
        "supportedEfforts": ["low", "medium", "high"],
        "thinkingTokenLimits": {
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          "min": 128
        }
      }
    },
    {
      "capabilities": ["function-call", "structured-output"],
      "contextWindow": 128000,
      "description": "The code generation model based on Qwen3 has powerful Coding Agent capabilities, excels in tool invocation and environment interaction, and can achieve autonomous programming with outstanding coding abilities while also possessing general capabilities.The model adopts tiered pricing.",
      "id": "qwen3-coder-plus-2025-07-22",
      "inputModalities": ["text"],
      "maxOutputTokens": 65536,
      "name": "Qwen3 Coder Plus 2025 07 22",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "cacheRead": {
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          "perMillionTokens": 0.54
        },
        "input": {
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        "output": {
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      }
    },
    {
      "capabilities": ["image-generation"],
      "description": "Image 4.0 Beta version, for testing purposes only. For production environment, it is recommended to use imagen-4.0-generate-preview-05-20.",
      "id": "imagen-4-0-ultra-generate-exp-05-20",
      "inputModalities": ["text", "image"],
      "name": "Imagen 4 0 Ultra Generate Exp 05 20",
      "outputModalities": ["image"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
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        "output": {
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          "perMillionTokens": 2
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      }
    },
    {
      "capabilities": ["embedding"],
      "description": "A 3.8-billion-parameter general vector model (embedding model) for state-of-the-art multilingual embeddings for edge deployment.",
      "id": "jina-embeddings-v5-text-nano",
      "inputModalities": ["text", "image"],
      "name": "Jina Embeddings V5 Text Nano",
      "outputModalities": ["text"],
      "ownedBy": "jina",
      "pricing": {
        "input": {
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          "perMillionTokens": 0.05
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          "perMillionTokens": 0.05
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    },
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      "description": "A 3.8-billion-parameter general vector (embedding) model providing state-of-the-art multilingual embeddings with task-specific adapters.",
      "id": "jina-embeddings-v5-text-small",
      "inputModalities": ["text", "image"],
      "name": "Jina Embeddings V5 Text Small",
      "outputModalities": ["text"],
      "ownedBy": "jina",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.05
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        "output": {
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          "perMillionTokens": 0.05
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      }
    },
    {
      "capabilities": ["image-generation"],
      "description": "Seedream 4.0 is a SOTA-level multimodal image creation model based on leading architecture. It breaks the creative boundaries of traditional text-to-image models by natively supporting text, single image, and multiple image inputs. Users can freely combine text and images to achieve various creative styles within the same model, such as multi-image fusion creation based on subject consistency, image editing, and set image generation, making image creation more flexible and controllable.\nSeedream 4.0 supports composite editing with up to 10 images in a single input. Through deep reasoning of prompt words, it automatically adapts the optimal image aspect ratio and generation quantity, enabling continuous output of up to 15 content-related images at one time. Additionally, the model significantly improves the accuracy and content diversity of Chinese generation, supports 4K ultra-high-definition output, and provides a one-stop solution from generation to editing for professional image creation.",
      "id": "doubao-seedream-4-0",
      "imageGeneration": {
        "modes": {
          "generate": {
            "supports": {
              "addWatermark": {
                "type": "switch"
              },
              "imageResolution": {
                "default": "2K",
                "options": ["1K", "2K", "4K"],
                "render": "chips",
                "type": "enum"
              },
              "seed": {
                "type": "text"
              }
            }
          }
        }
      },
      "inputModalities": ["text", "image"],
      "name": "Doubao Seedream 4 0",
      "outputModalities": ["image"],
      "ownedBy": "bytedance",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0
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      }
    },
    {
      "capabilities": ["embedding"],
      "description": "Embedding-V1 is a text representation model based on Baidu's Wenxin large model technology, capable of converting text into numerical vector forms for applications such as text retrieval, information recommendation, and knowledge mining. Embedding-V1 provides an Embeddings interface that generates corresponding vector representations based on the input content. By calling this interface, you can input text into the model and obtain the corresponding vector representations for subsequent text processing and analysis.",
      "id": "embedding-v1",
      "inputModalities": ["text"],
      "name": "Embedding V1",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.068
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.068
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      }
    },
    {
      "capabilities": ["function-call", "structured-output"],
      "contextWindow": 135000,
      "description": "Wenxin 4.5 Turbo also has significant improvements in hallucination reduction, logical reasoning, and coding capabilities. Compared to Wenxin 4.5, it is faster and more affordable.",
      "id": "ernie-4-5-turbo-latest",
      "inputModalities": ["text", "image"],
      "maxOutputTokens": 12000,
      "name": "Ernie 4 5 Turbo Latest",
      "outputModalities": ["text"],
      "ownedBy": "baidu",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.11
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.44
        }
      }
    },
    {
      "capabilities": ["function-call", "structured-output", "image-generation"],
      "description": "Baidu's self-developed ERNIE iRAG Edit image editing model supports operations based on images such as erase (object removal), repaint (object redrawing), and variation (variant generation).",
      "id": "ernie-irag-edit",
      "inputModalities": ["text", "image"],
      "name": "Ernie Irag Edit",
      "outputModalities": ["image"],
      "ownedBy": "baidu",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0
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      }
    },
    {
      "capabilities": ["function-call", "reasoning"],
      "description": "GLM-4.5-X is the high-speed version of GLM-4.5, offering powerful performance with a generation speed of up to 100 tokens per second.",
      "id": "glm-4-5-x",
      "inputModalities": ["text"],
      "name": "Glm 4 5 X",
      "outputModalities": ["text"],
      "ownedBy": "zhipu",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.44
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 2.2
        },
        "output": {
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          "perMillionTokens": 8.91
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      },
      "reasoning": {
        "supportedEfforts": ["none"]
      }
    },
    {
      "capabilities": ["function-call", "image-recognition"],
      "description": "The GME-Qwen2VL series is a unified multimodal Embedding model trained based on the Qwen2-VL multimodal large language model (MLLMs). The GME model supports three types of inputs: text, images, and image-text pairs. All these input types can generate universal vector representations and exhibit excellent retrieval performance.",
      "id": "gme-qwen2-vl-instruct",
      "inputModalities": ["text", "image", "video"],
      "name": "Gme Qwen2 VL Instruct",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.138
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.138
        }
      }
    },
    {
      "capabilities": ["embedding", "rerank"],
      "description": "gte-rerank-v2 is a multilingual unified text ranking model developed by Tongyi Lab, covering multiple major languages worldwide and providing high-quality text ranking services. It is typically used in scenarios such as semantic retrieval and RAG, and can simply and effectively improve text retrieval performance. Given a query and a set of candidate texts (documents), the model ranks the candidates from highest to lowest based on their semantic relevance to the query.",
      "id": "gte-rerank-v2",
      "inputModalities": ["text", "image"],
      "name": "Gte Rerank V2",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.11
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.11
        }
      }
    },
    {
      "capabilities": ["image-generation"],
      "description": "Baidu's self-developed ERNIE iRAG (ERNIE image-based RAG), a retrieval-augmented text-to-image technology, combines Baidu Search's hundreds of millions of image resources with powerful foundational model capabilities to generate various ultra-realistic images. The overall effect far surpasses native text-to-image systems, eliminating the typical AI feel while maintaining low costs. ERNIE iRAG features no hallucinations, ultra-realism, and instant usability.",
      "id": "irag-1-0",
      "inputModalities": ["text"],
      "name": "Irag 1 0",
      "outputModalities": ["image"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0
        }
      },
      "ownedBy": "baidu",
      "family": "ernie"
    },
    {
      "capabilities": ["reasoning", "web-search"],
      "contextWindow": 1000000,
      "description": "DeepSearch combines search, reading, and reasoning capabilities to pursue the best possible answer. It's fully compatible with OpenAI's Chat API format—just replace api.openai.com with aihubmix.com to get started.  \nThe stream will return the thinking process.",
      "id": "jina-deepsearch-v1",
      "inputModalities": ["text", "image"],
      "name": "Jina Deepsearch V1",
      "outputModalities": ["text"],
      "ownedBy": "jina",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.05
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.05
        }
      }
    },
    {
      "capabilities": ["embedding"],
      "description": "A general-purpose vector model with 3.8 billion parameters, used for multimodal and multilingual retrieval, supporting both unidirectional and multi-vector embedding outputs.",
      "id": "jina-embeddings-v4",
      "inputModalities": ["text", "image"],
      "name": "Jina Embeddings V4",
      "outputModalities": ["text"],
      "ownedBy": "jina",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.05
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.05
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      }
    },
    {
      "capabilities": ["rerank"],
      "contextWindow": 131000,
      "description": "Multimodal multilingual document reranker, 131K context, 0.6B parameters, for visual document sorting.",
      "id": "jina-reranker-v3",
      "inputModalities": ["text", "image"],
      "name": "Jina Reranker V3",
      "outputModalities": ["text"],
      "ownedBy": "jina",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.05
        },
        "output": {
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          "perMillionTokens": 0.05
        }
      }
    },
    {
      "capabilities": ["image-recognition", "file-input", "image-generation"],
      "description": "Qwen-Image is a foundational image generation model in the Qwen series, achieving significant progress in complex text rendering and precise image editing. Experiments show that the model has strong general capabilities in image generation and editing, especially excelling in Chinese text rendering.",
      "id": "qwen-image",
      "imageGeneration": {
        "modes": {
          "generate": {
            "supports": {
              "numImages": {
                "default": 1,
                "max": 1,
                "min": 1,
                "type": "range"
              },
              "size": {
                "default": "1664x928",
                "options": ["1664x928", "1472x1140", "1328x1328", "1140x1472", "928x1664"],
                "render": "chips",
                "type": "enum"
              }
            }
          }
        }
      },
      "inputModalities": ["text", "image"],
      "name": "Qwen Image",
      "outputModalities": ["image"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0
        }
      },
      "contextWindow": 0,
      "maxOutputTokens": 0,
      "openWeights": false,
      "family": "qwen",
      "reasoning": {
        "supportedEfforts": ["none"]
      }
    },
    {
      "capabilities": ["image-recognition", "file-input", "image-generation"],
      "description": "Qwen-Image-Edit is the image editing version of Qwen-Image. Based on the 20B Qwen-Image model, Qwen-Image-Edit successfully extends Qwen-Image's unique text rendering capabilities to image editing tasks, achieving precise text editing. Additionally, Qwen-Image-Edit can input the same image into Qwen2.5-VL (for visual semantic control) and the VAE encoder (for visual appearance control), enabling both semantic and appearance editing functionalities.",
      "id": "qwen-image-edit",
      "imageGeneration": {
        "modes": {
          "edit": {
            "supports": {
              "addWatermark": {
                "type": "switch"
              },
              "outputFormat": {
                "options": ["jpeg", "png", "webp"],
                "type": "enum"
              },
              "seed": {
                "type": "text"
              }
            },
            "vendorTransport": {
              "endpoint": "/v3/async/qwen-image-edit"
            }
          }
        }
      },
      "inputModalities": ["text", "image"],
      "name": "Qwen Image Edit",
      "outputModalities": ["image"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0
        }
      },
      "contextWindow": 0,
      "maxOutputTokens": 0,
      "openWeights": false,
      "family": "qwen",
      "reasoning": {
        "supportedEfforts": ["none"]
      }
    },
    {
      "capabilities": ["image-generation"],
      "description": "Qwen-Image is a foundational image generation model in the Qwen series, achieving significant progress in complex text rendering and precise image editing. Experiments show that the model has strong general capabilities in image generation and editing, especially excelling in Chinese text rendering.",
      "id": "qwen-image-plus",
      "inputModalities": ["text", "image"],
      "name": "Qwen Image Plus",
      "outputModalities": ["image"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0
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    },
    {
      "capabilities": ["function-call", "rerank", "reasoning"],
      "contextWindow": 16000,
      "description": "Based on the dense foundational model of the Qwen3 series, it is specifically designed for ranking tasks. It inherits the base model’s outstanding multilingual capabilities, long-text understanding, and reasoning skills, achieving significant advancements in ranking tasks.",
      "id": "qwen3-reranker",
      "inputModalities": ["text", "image"],
      "maxOutputTokens": 8000,
      "name": "Qwen3 Reranker",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.11
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.11
        }
      },
      "reasoning": {
        "supportedEfforts": ["none", "low", "medium", "high"],
        "thinkingTokenLimits": {
          "max": 38912,
          "min": 1024
        }
      }
    },
    {
      "id": "tao-8k",
      "inputModalities": ["text"],
      "name": "Tao 8k",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.068
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.068
        }
      }
    },
    {
      "capabilities": ["rerank"],
      "description": "Based on the dense foundational model of the Qwen3 series, it is specifically designed for ranking tasks. It inherits the base model’s outstanding multilingual capabilities, long-text understanding, and reasoning skills, achieving significant advancements in ranking tasks.",
      "id": "bce-reranker-base",
      "inputModalities": ["text", "image"],
      "name": "Bce Reranker Base",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.068
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.068
        }
      }
    },
    {
      "description": "Multi-modal Embeddings Model, multilingual, 1024-dimensional, 865M parameters.",
      "id": "jina-clip-v2",
      "inputModalities": ["text", "image"],
      "name": "Jina Clip V2",
      "outputModalities": ["text"],
      "ownedBy": "jina",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.05
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.05
        }
      }
    },
    {
      "capabilities": ["rerank"],
      "description": "Multimodal multilingual document reranker, 10K context, 2.4B parameters, for visual document sorting.",
      "id": "jina-reranker-m0",
      "inputModalities": ["text", "image"],
      "name": "Jina Reranker M0",
      "outputModalities": ["text"],
      "ownedBy": "jina",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.05
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.05
        }
      }
    },
    {
      "description": "Multi-language ColBERT embeddings model, 560M parameters, used for embedding and reranking.",
      "id": "jina-colbert-v2",
      "inputModalities": ["text"],
      "name": "Jina Colbert V2",
      "outputModalities": ["text"],
      "ownedBy": "jina",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.05
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.05
        }
      }
    },
    {
      "capabilities": ["function-call", "structured-output", "image-recognition", "web-search"],
      "contextWindow": 128000,
      "description": "GPT-4o Search Previewis a specialized model for web search in Chat Completions. It is trained to understand and execute web search queries.",
      "id": "gpt-4o-search-preview",
      "inputModalities": ["text"],
      "maxOutputTokens": 16384,
      "name": "OpenAI: GPT-4o Search Preview",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 1.25
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 2.5
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        "output": {
          "currency": "USD",
          "perMillionTokens": 10
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      },
      "openWeights": false,
      "reasoning": {
        "supportedEfforts": ["none"]
      }
    },
    {
      "capabilities": ["embedding"],
      "description": "Text Embeddings Model, multilingual, 1024-dimensional, 570M parameters.",
      "id": "jina-embeddings-v3",
      "inputModalities": ["text"],
      "name": "Jina Embeddings V3",
      "outputModalities": ["text"],
      "ownedBy": "jina",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.05
        },
        "output": {
          "currency": "USD",
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      }
    },
    {
      "capabilities": ["function-call", "structured-output"],
      "contextWindow": 160000,
      "description": "Wenxin Large Model 4.5 is a next-generation native multimodal foundational model independently developed by Baidu. It achieves collaborative optimization through joint modeling of multiple modalities, demonstrating excellent multimodal understanding capabilities; it possesses more advanced language abilities, with comprehensive improvements in comprehension, generation, logic, and memory, as well as significant enhancements in hallucination reduction, logical reasoning, and coding capabilities.ERNIE-4.5-21B-A3B is an aligned open-source model with a MoE structure, having a total of 21 billion parameters and 3 billion activated parameters.",
      "id": "ernie-4-5",
      "inputModalities": ["text", "image"],
      "maxOutputTokens": 64000,
      "name": "Ernie 4 5",
      "outputModalities": ["text"],
      "ownedBy": "baidu",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.068
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.272
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      }
    },
    {
      "capabilities": ["function-call", "structured-output", "image-recognition"],
      "contextWindow": 139000,
      "description": "The new version of the Wenxin Yiyan large model significantly improves capabilities in image understanding, creation, translation, and coding. It supports a context length of up to 32K tokens for the first time, with a notable reduction in the latency of the first token.",
      "id": "ernie-4-5-turbo-vl",
      "inputModalities": ["text", "image"],
      "maxOutputTokens": 16000,
      "name": "Ernie 4 5 Turbo VL",
      "outputModalities": ["text"],
      "ownedBy": "baidu",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.4
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 1.2
        }
      }
    },
    {
      "capabilities": ["image-generation", "function-call", "image-recognition", "web-search"],
      "description": "Gemini 2.0 Flash EXP is the official preview version of the drawing model. Compared to Imagen 3.0, Gemini’s image generation is better suited for scenarios that require contextual understanding and reasoning, rather than the pursuit of ultimate artistic performance and visual quality.",
      "id": "gemini-2-0-flash-preview-image-generation",
      "inputModalities": ["text", "image"],
      "name": "Gemini 2 0 Flash Preview Image Generation",
      "outputModalities": ["image"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.1
        },
        "output": {
          "currency": "USD",
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        }
      }
    },
    {
      "capabilities": ["image-generation"],
      "description": "Generate and edit images through both text and image prompts. Flux.1 Kontext is a multimodal flow matching model that enables both text-to-image generation and in-context image editing. Modify images while maintaining character consistency and performing local edits up to 8x faster than other leading models.",
      "id": "flux.1-kontext-pro",
      "inputModalities": ["text", "image"],
      "name": "Flux.1 Kontext Pro",
      "outputModalities": ["image"],
      "ownedBy": "bfl",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 40
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 40
        }
      }
    },
    {
      "capabilities": ["image-generation"],
      "description": "FLUX-1.1-pro is an AI image generation tool for professional creators and content workflows. It understands complex semantic and structural instructions to deliver high consistency, multi-image coherence, and style customization from text prompts.",
      "id": "flux-1-1-pro",
      "inputModalities": ["text", "image"],
      "name": "Flux 1 1 Pro",
      "outputModalities": ["image"],
      "ownedBy": "bfl",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 40
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 40
        }
      }
    },
    {
      "capabilities": ["function-call", "structured-output", "reasoning", "image-recognition"],
      "contextWindow": 256000,
      "description": "Doubao-Seed-1.6-lite is a brand new multimodal deep reasoning model that supports adjustable reasoning effort, with four modes: Minimal, Low, Medium, and High. It offers better cost performance, making it the best choice for common tasks, with a context window of up to 256k.",
      "id": "doubao-seed-1-6-lite",
      "inputModalities": ["text", "image", "video"],
      "maxOutputTokens": 32000,
      "name": "Doubao Seed 1 6 Lite",
      "outputModalities": ["text"],
      "ownedBy": "bytedance",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.0164
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.082
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.656
        }
      }
    },
    {
      "capabilities": ["reasoning", "function-call"],
      "description": "cerebras",
      "id": "qwen-3-a22b-thinking-2507",
      "inputModalities": ["text"],
      "name": "Qwen 3 A22b Thinking 2507",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.28
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2.8
        }
      }
    },
    {
      "capabilities": ["function-call", "image-recognition"],
      "description": "The model provider is the Sophnet platform. Qwen2-VL-72B-Instruct is the latest iteration in the Qwen2-VL series launched by Alibaba Cloud, representing nearly a year of innovative achievements. This model has 72 billion parameters and can understand images of various resolutions and aspect ratios. Additionally, it supports video understanding of over 20 minutes, enabling high-quality video question answering, dialogue, and content creation, along with complex reasoning and decision-making capabilities.\n\n- State-of-the-art image understanding: capable of processing images of various resolutions and aspect ratios, performing excellently across multiple visual understanding benchmarks.\n- Long video understanding: supports video comprehension exceeding 20 minutes, enabling high-quality video Q&A, dialogues, and content creation.\n- Agent operation capability: equipped with complex reasoning and decision-making abilities, it can integrate with devices such as phones and robots to perform automated operations based on visual environments and textual instructions.\n- Multilingual support: in addition to English and Chinese, it supports understanding text in images in multiple languages, including most European languages, Japanese, Korean, Arabic, Vietnamese, and more.\n- Supports a maximum context length of 128K tokens, offering powerful processing capabilities.",
      "id": "qwen2-vl-instruct",
      "inputModalities": ["text", "image", "video"],
      "name": "Qwen2 VL Instruct",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2.18
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 6.54
        }
      }
    },
    {
      "capabilities": ["embedding"],
      "contextWindow": 8000,
      "description": "A text vector model that converts input text information into vector representations so that, in conjunction with a vector database, it provides an external knowledge base for the large model, thereby improving the accuracy of the model’s reasoning.",
      "id": "embedding-2",
      "inputModalities": ["text"],
      "name": "Embedding 2",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.0686
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.0686
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      }
    },
    {
      "capabilities": ["embedding"],
      "contextWindow": 8000,
      "description": "A text vector model that converts input text into vector representations to work with a vector database and provide an external knowledge base for a large model. The model supports custom vector dimensions; it is recommended to choose 256, 512, 1024, or 2048 dimensions.",
      "id": "embedding-3",
      "inputModalities": ["text"],
      "name": "Embedding 3",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.0686
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.0686
        }
      }
    },
    {
      "capabilities": ["reasoning", "function-call", "image-recognition"],
      "description": "Doubao-Seed-1.6 is a brand new multimodal deep reasoning model that supports four types of reasoning effort: minimal, low, medium, and high. It offers stronger model performance, serving complex tasks and challenging scenarios. It supports a 256k context window, with output length up to a maximum of 32k tokens.",
      "id": "doubao-seed-1-6-250615",
      "inputModalities": ["text"],
      "name": "Doubao Seed 1 6 250615",
      "outputModalities": ["text"],
      "ownedBy": "bytedance",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.036
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.18
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2.52
        }
      }
    },
    {
      "capabilities": ["reasoning", "function-call", "image-recognition"],
      "description": "Doubao-Seed-1.6-flash is an extremely fast multimodal deep thinking model, with TPOT requiring only 10ms. It supports both text and visual understanding, with its text comprehension skills surpassing the previous generation lite model and its visual understanding on par with competitor's pro series models. It supports a 256k context window and an output length of up to 16k tokens.",
      "id": "doubao-seed-1-6-flash-250615",
      "inputModalities": ["text"],
      "name": "Doubao Seed 1 6 Flash 250615",
      "outputModalities": ["text"],
      "ownedBy": "bytedance",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.0088
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.044
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.44
        }
      }
    },
    {
      "capabilities": ["reasoning", "function-call", "image-recognition"],
      "description": "The Doubao-Seed-1.6-thinking model has significantly enhanced reasoning capabilities. Compared with Doubao-1.5-thinking-pro, it has further improvements in fundamental abilities such as coding, mathematics, and logical reasoning, and now also supports visual understanding. It supports a 256k context window, with output length supporting up to 16k tokens.",
      "id": "doubao-seed-1-6-thinking-250615",
      "inputModalities": ["text"],
      "name": "Doubao Seed 1 6 Thinking 250615",
      "outputModalities": ["text"],
      "ownedBy": "bytedance",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.036
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.18
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2.52
        }
      }
    },
    {
      "capabilities": ["image-generation"],
      "description": "First Taste of GPT-4o's Image Generation API: Perfectly mirrors the web version's raw image creation capabilities, supporting both text-to-image and image+text-to-image generation. Each creation costs as little as $0.009.",
      "id": "gpt-4o-image-vip",
      "inputModalities": ["text", "image"],
      "name": "GPT 4o Image Vip",
      "outputModalities": ["image"],
      "ownedBy": "openai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 7
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 7
        }
      }
    },
    {
      "capabilities": ["image-generation"],
      "description": "First Taste of GPT-4o's Image Generation API: Perfectly mirrors the web version's raw image creation capabilities, supporting both text-to-image and image+text-to-image generation. Each creation costs as little as $0.005.",
      "id": "gpt-4o-image",
      "inputModalities": ["text", "image"],
      "name": "GPT 4o Image",
      "outputModalities": ["image"],
      "ownedBy": "openai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 3
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 3
        }
      }
    },
    {
      "capabilities": ["function-call", "image-recognition", "file-input", "web-search"],
      "description": "OpenAI’s latest TTS model, gpt-4o-mini-tts, uses the same API endpoint (/v1/audio/speech) as tts-1. However, OpenAI introduced a new pricing method without providing billing details via API, causing discrepancies between official pricing and aihubmix’s charges—some requests may cost more, others less. Avoid using this model if precise billing accuracy is essential.",
      "id": "gpt-4o-mini-tts",
      "inputModalities": ["audio"],
      "name": "GPT 4o Mini TTS",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.6
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.6
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 12
        }
      },
      "contextWindow": 128000,
      "maxOutputTokens": 16384,
      "openWeights": false,
      "family": "gpt-mini",
      "reasoning": {
        "supportedEfforts": ["none"]
      }
    },
    {
      "capabilities": ["reasoning", "function-call", "image-recognition", "web-search"],
      "description": "The latest version, Gemini 2.0 Flash Thinking mode, is an experimental model designed to generate the \"thought process\" that the model goes through during its responses. Therefore, Gemini 2.0 Flash Thinking mode has stronger reasoning capabilities in its responses compared to the base Gemini 2.0 Flash model.",
      "id": "gemini-2-0-flash-thinking-exp-01-21",
      "inputModalities": ["text", "image", "audio", "video"],
      "name": "Gemini 2 0 Flash Thinking Exp 01 21",
      "outputModalities": ["text"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.076
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.304
        }
      }
    },
    {
      "contextWindow": 119000,
      "description": "The Wenxin large model X1.1 has made significant improvements in question answering, tool invocation, intelligent agents, instruction following, logical reasoning, mathematics, and coding tasks, with notable enhancements in factual accuracy. The context length has been extended to 64K tokens, supporting longer inputs and dialogue history, which improves the coherence of long-chain reasoning while maintaining response speed.",
      "id": "ernie-x1-1-preview",
      "inputModalities": ["text"],
      "maxOutputTokens": 64000,
      "name": "Ernie X1 1 Preview",
      "outputModalities": ["text"],
      "ownedBy": "baidu",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.136
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.544
        }
      }
    },
    {
      "capabilities": ["function-call", "structured-output", "embedding"],
      "description": "bge-large-en, open-sourced by the Beijing Academy of Artificial Intelligence (BAAI), is currently the most powerful vector representation model for Chinese tasks, with its semantic representation capabilities comprehensively surpassing those of similar open-source models.",
      "id": "bge-large-en",
      "inputModalities": ["text", "image"],
      "name": "Bge Large En",
      "outputModalities": ["text"],
      "ownedBy": "baai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.068
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.068
        }
      }
    },
    {
      "capabilities": ["function-call", "structured-output", "embedding"],
      "description": "bge-large-zh, open-sourced by the Beijing Academy of Artificial Intelligence (BAAI), is currently the most powerful vector representation model for Chinese tasks, with its semantic representation capabilities comprehensively surpassing those of similar open-source models.",
      "id": "bge-large-zh",
      "inputModalities": ["text", "image"],
      "name": "Bge Large Zh",
      "outputModalities": ["text"],
      "ownedBy": "baai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.068
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.068
        }
      }
    },
    {
      "capabilities": ["function-call", "structured-output"],
      "description": "Wenxin 4.5 Turbo also shows significant enhancements in reducing hallucinations, logical reasoning, and coding capabilities. Compared to Wenxin 4.5, it is faster and more cost-effective.",
      "id": "ernie-4-5-turbo-128k-preview",
      "inputModalities": ["text", "image"],
      "name": "Ernie 4 5 Turbo 128k Preview",
      "outputModalities": ["text"],
      "ownedBy": "baidu",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.108
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.432
        }
      }
    },
    {
      "capabilities": ["reasoning", "function-call", "structured-output"],
      "contextWindow": 50500,
      "description": "Wenxin Large Model X1 possesses enhanced abilities in understanding, planning, reflection, and evolution. As a more comprehensive deep-thinking model, Wenxin X1 combines accuracy, creativity, and literary elegance, excelling particularly in Chinese knowledge Q&A, literary creation, document writing, daily conversations, logical reasoning, complex calculations, and tool invocation.",
      "id": "ernie-x1-turbo",
      "inputModalities": ["text"],
      "maxOutputTokens": 28000,
      "name": "Ernie X1 Turbo",
      "outputModalities": ["text"],
      "ownedBy": "baidu",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.136
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.544
        }
      }
    },
    {
      "description": "Provided by chutes.ai.",
      "id": "moonlight-a3b-instruct",
      "inputModalities": ["text"],
      "name": "Moonlight A3b Instruct",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.2
        }
      }
    },
    {
      "capabilities": ["reasoning", "function-call", "image-recognition"],
      "description": "OpenAI new model",
      "id": "o1-global",
      "inputModalities": ["text"],
      "name": "O1 Global",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 7.5
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 15
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 60
        }
      },
      "reasoning": {
        "supportedEfforts": ["low", "medium", "high"]
      }
    },
    {
      "capabilities": ["image-recognition"],
      "description": "The Qianfan-QI-VL model is a proprietary image quality inspection and visual understanding large model (Quality Inspection Large Vision Language Model, Qianfan-QI-VL) developed by Baidu Cloud’s Qianfan platform. It is designed for quality inspection of product images uploaded in e-commerce scenarios, with detection capabilities including AIGC human defect detection, mosaic recognition, watermark recognition, and trademark detection.",
      "id": "qianfan-qi-vl",
      "inputModalities": ["text"],
      "name": "Qianfan Qi VL",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.6
        }
      }
    },
    {
      "description": "Google's latest experimental model, currently Google's most powerful model.",
      "id": "gemini-exp-1206",
      "inputModalities": ["text"],
      "name": "Gemini Exp 1206",
      "outputModalities": ["text"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 1.25
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 5
        }
      }
    },
    {
      "capabilities": ["function-call", "image-recognition", "web-search"],
      "id": "gpt-4o-zh",
      "inputModalities": ["text", "image"],
      "name": "GPT 4o Zh",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2.5
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 10
        }
      }
    },
    {
      "capabilities": ["function-call"],
      "description": "Qwen 2.5-Max latest model",
      "id": "qwen-max-0125",
      "inputModalities": ["text"],
      "name": "Qwen Max 0125",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.38
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 1.52
        }
      }
    },
    {
      "capabilities": ["function-call", "structured-output", "embedding"],
      "description": "BAAI/bge-large-zh-v1.5 is a large Chinese text embedding model and part of the BGE (BAAI General Embedding) series. It performs excellently on the C-MTEB benchmark, achieving an average score of 64.53 across 31 datasets, with outstanding results in tasks such as retrieval, semantic similarity, and text pair classification. The model supports a maximum input length of 512 tokens and is suitable for various Chinese natural language processing tasks, such as text retrieval and semantic similarity computation.",
      "id": "bge-large-zh-v1-5",
      "inputModalities": ["text", "image"],
      "name": "Bge Large Zh V1 5",
      "outputModalities": ["text"],
      "ownedBy": "baai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.034
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.034
        }
      }
    },
    {
      "capabilities": ["function-call", "image-recognition", "web-search"],
      "description": "Gemini 2.0 Flash lightweight version",
      "id": "gemini-2-0-flash-lite-preview-02-05",
      "inputModalities": ["text"],
      "name": "Gemini 2 0 Flash Lite Preview 02 05",
      "outputModalities": ["text"],
      "ownedBy": "google",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.075
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.075
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.3
        }
      }
    },
    {
      "capabilities": ["image-generation"],
      "description": "Fast and high-quality — top image quality in just 11 seconds per piece, with almost no extra time for batch generation.\nFlexible ratios — supports ultra-wide and tall formats like 3:1, 2:1, offering diverse perspectives.\nUnique strengths — outstanding design capabilities in the V3 and V2 series, with powerful text rendering (Chinese support coming soon).\nPrecise local editing — fine-tuned mask control for area redrawing (edit) and easy background replacement (replace-background).",
      "id": "v3",
      "inputModalities": ["text", "image"],
      "name": "V3",
      "outputModalities": ["image"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      },
      "ownedBy": "ideogram-ai",
      "family": "ideogram-ai"
    },
    {
      "capabilities": ["image-generation"],
      "description": "The Ideogram AI drawing interface is now live. This model boasts powerful text-to-image capabilities, supporting endpoints are: /generate, /remix, /edit.\nThis model is the stable V_2 version, highly recommended for editing.\nUS $0.08/ 1 IMG.\nFor usage examples and pricing details, refer to the documentation at https://docs.aihubmix.com/cn/api/IdeogramAI.",
      "id": "v_2",
      "inputModalities": ["text", "image"],
      "name": "V_2",
      "outputModalities": ["image"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      },
      "ownedBy": "ideogram-ai",
      "family": "ideogram-ai"
    },
    {
      "capabilities": ["image-generation"],
      "description": "The Ideogram AI drawing interface is now live. This model boasts powerful text-to-image capabilities, supporting endpoints are: /generate, /remix, /edit.\nThis model is the fast version of V_2, offering increased speed at the slight expense of quality.\nUS $0.05/ IMG.\nFor usage examples and pricing details, refer to the documentation at https://docs.aihubmix.com/cn/api/IdeogramAI.",
      "id": "v_2_turbo",
      "inputModalities": ["text", "image"],
      "name": "V_2_turbo",
      "outputModalities": ["image"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      },
      "ownedBy": "ideogram-ai",
      "family": "ideogram-ai"
    },
    {
      "capabilities": ["image-generation"],
      "description": "The Ideogram AI drawing interface is now live. This model boasts powerful text-to-image capabilities, supporting endpoints are: /generate, /remix.\nThis model is the fast version of V_2, faster and cheaper.\nUS $0.04/ IMG.\nFor usage examples and pricing details, refer to the documentation at https://docs.aihubmix.com/cn/api/IdeogramAI.",
      "id": "v_2a",
      "inputModalities": ["text", "image"],
      "name": "V_2a",
      "outputModalities": ["image"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      },
      "ownedBy": "ideogram-ai",
      "family": "ideogram-ai"
    },
    {
      "capabilities": ["image-generation"],
      "description": "The Ideogram AI drawing interface is now live. This model boasts powerful text-to-image capabilities, supporting endpoints are: /generate, /remix.\nThis model is the ultra-fast version of V_2, delivering the highest speed while slightly reducing quality.\nUS $0.025/ IMG.\nFor usage examples and pricing details, refer to the documentation at https://docs.aihubmix.com/cn/api/IdeogramAI.",
      "id": "v_2a_turbo",
      "inputModalities": ["text", "image"],
      "name": "V_2a_turbo",
      "outputModalities": ["image"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      },
      "ownedBy": "ideogram-ai",
      "family": "ideogram-ai"
    },
    {
      "capabilities": ["image-generation"],
      "description": "V_1 is a text-to-image model in the Ideogram series. It delivers strong text rendering capabilities, high photorealistic image quality, and precise prompt adherence. The model also introduces Magic Prompt, a new feature that automatically refines input prompts to generate more detailed and creative visuals.",
      "id": "v_1",
      "inputModalities": ["text", "image"],
      "name": "V_1",
      "outputModalities": ["image"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      },
      "ownedBy": "ideogram-ai",
      "family": "ideogram-ai"
    },
    {
      "capabilities": ["image-generation"],
      "description": "The Ideogram AI drawing interface is now live. This model boasts powerful text-to-image capabilities, supporting endpoints are: /generate, /remix.\nThis model is the ultra-fast version of the original V_1, offering increased speed at the slight expense of quality.\nUS $0.02/ IMG.\nFor usage examples and pricing details, refer to the documentation at https://docs.aihubmix.com/cn/api/IdeogramAI.",
      "id": "v_1_turbo",
      "inputModalities": ["text", "image"],
      "name": "V_1_turbo",
      "outputModalities": ["image"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      },
      "ownedBy": "ideogram-ai",
      "family": "ideogram-ai"
    },
    {
      "capabilities": ["embedding"],
      "description": "doubao-embedding-large-text-240915\nDoubao Embedding is a semantic vectorization model developed by ByteDance, primarily designed for vector search scenarios. It supports both Chinese and English languages and has a maximum context length of approximately 4K tokens.",
      "id": "doubao-embedding-large-text-240915",
      "inputModalities": ["text"],
      "name": "Doubao Embedding Large Text 240915",
      "outputModalities": ["text"],
      "ownedBy": "bytedance",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.1
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.1
        }
      }
    },
    {
      "capabilities": ["function-call", "reasoning", "image-recognition", "file-input"],
      "description": "The latest kimi model.",
      "id": "kimi-thinking-preview",
      "inputModalities": ["text"],
      "name": "Kimi Thinking Preview",
      "outputModalities": ["text"],
      "ownedBy": "moonshot",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 30
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 30
        }
      },
      "contextWindow": 256000,
      "maxOutputTokens": 65536,
      "openWeights": false,
      "reasoning": {
        "supportedEfforts": ["none", "auto"]
      }
    },
    {
      "capabilities": ["function-call", "structured-output", "reasoning"],
      "contextWindow": 1000000,
      "description": "Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed, and cost combination.",
      "id": "qwen-plus-2025-07-28",
      "inputModalities": ["text"],
      "maxOutputTokens": 32768,
      "name": "Qwen: Qwen Plus 0728",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.11
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.39999999999999997
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 1.2
        }
      },
      "reasoning": {
        "supportedEfforts": ["none", "low", "medium", "high"],
        "thinkingTokenLimits": {
          "max": 81920,
          "min": 0
        }
      },
      "openWeights": true
    },
    {
      "capabilities": ["function-call", "reasoning"],
      "description": "The Qwen series models with balanced capabilities have inference performance and speed between Qwen-Max and Qwen-Turbo, making them suitable for moderately complex tasks. This model is a dynamically updated version, and updates will not be announced in advance. The current version is qwen-plus-2025-04-28.The model adopts tiered pricing.",
      "id": "qwen-plus-latest",
      "inputModalities": ["text"],
      "name": "Qwen Plus Latest",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.11
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.11
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.275
        }
      },
      "reasoning": {
        "supportedEfforts": ["none", "low", "medium", "high"],
        "thinkingTokenLimits": {
          "max": 81920,
          "min": 0
        }
      },
      "contextWindow": 1000000,
      "maxOutputTokens": 32768,
      "openWeights": false
    },
    {
      "description": "Step3 is a multimodal reasoning model released by StepFun. It uses a Mixture‑of‑Experts (MoE) architecture with 321 billion total parameters and 38 billion activation parameters. The model follows an end‑to‑end design that reduces decoding cost while delivering top‑tier performance on vision‑language reasoning tasks. Thanks to the combined use of Multi‑Head Factorized Attention (MFA) and Attention‑FFN Decoupling (AFD), Step3 remains highly efficient on both flagship and low‑end accelerators. During pre‑training, it processed over 20 trillion text tokens and 4 trillion image‑text mixed tokens, covering more than ten languages. On benchmarks for mathematics, code, and multimodal tasks, Step3 consistently outperforms other open‑source models.",
      "id": "step3",
      "inputModalities": ["text"],
      "name": "Step3",
      "outputModalities": ["text"],
      "ownedBy": "stepfun",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 1.1
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2.75
        }
      }
    },
    {
      "capabilities": ["embedding"],
      "description": "This is the Tongyi Laboratory's multilingual unified text vector model trained based on Qwen3, which significantly improves performance in text retrieval, clustering, and classification compared to version V3; it achieves a 15% to 40% improvement on evaluation tasks such as MTEB multilingual, Chinese-English, and code retrieval; supports user-defined vector dimensions ranging from 64 to 2048.",
      "id": "text-embedding-v4",
      "inputModalities": ["text"],
      "name": "Text Embedding V4",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.08
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.08
        }
      }
    },
    {
      "capabilities": ["function-call", "reasoning"],
      "description": "The Qwen series model with the fastest speed and lowest cost, suitable for simple tasks. This model is a dynamically updated version, and updates will not be announced in advance. The model's overall Chinese and English abilities have been significantly improved, human preference alignment has been greatly enhanced, inference capability and complex instruction understanding have been substantially strengthened, performance on difficult tasks is better, and mathematics and coding skills have been significantly improved. The current version is qwen-turbo-2025-04-28.",
      "id": "qwen-turbo-latest",
      "inputModalities": ["text"],
      "name": "Qwen Turbo Latest",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.046
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.92
        }
      },
      "reasoning": {
        "supportedEfforts": ["none", "low", "medium", "high"],
        "thinkingTokenLimits": {
          "max": 38912,
          "min": 0
        }
      }
    },
    {
      "capabilities": ["embedding"],
      "description": "doubao-embedding-text-240715\nDoubao Embedding is a semantic vectorization model developed by ByteDance, primarily designed for vector search scenarios. It supports both Chinese and English languages and has a maximum context length of approximately 4K tokens.",
      "id": "doubao-embedding-text-240715",
      "inputModalities": ["text"],
      "name": "Doubao Embedding Text 240715",
      "outputModalities": ["text"],
      "ownedBy": "bytedance",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.7
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.7
        }
      }
    },
    {
      "capabilities": ["reasoning", "function-call"],
      "description": "Openly deployed by chutes.ai; inference with FP8; zero is the initial preliminary version of R1 without optimizations and is not recommended for use unless for research purposes.",
      "id": "deepseek-r1-zero",
      "inputModalities": ["text"],
      "name": "Deepseek R1 Zero",
      "outputModalities": ["text"],
      "ownedBy": "deepseek",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2.2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2.2
        }
      }
    },
    {
      "capabilities": ["function-call", "web-search"],
      "id": "grok-3-fast-beta",
      "inputModalities": ["text"],
      "name": "Grok 3 Fast Beta",
      "outputModalities": ["text"],
      "ownedBy": "xai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 5.5
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 27.5
        }
      }
    },
    {
      "capabilities": ["function-call", "reasoning"],
      "description": "The Qwen3 series Turbo model effectively integrates thinking and non-thinking modes, allowing seamless switching between modes during conversations. With a smaller parameter size, its reasoning ability rivals that of QwQ-32B, and its general capabilities significantly surpass those of Qwen2.5-Turbo, reaching state-of-the-art (SOTA) levels among models of the same scale. This version is a snapshot model as of April 28, 2025.",
      "id": "qwen-turbo-2025-04-28",
      "inputModalities": ["text"],
      "name": "Qwen Turbo 2025 04 28",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.046
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.92
        }
      },
      "reasoning": {
        "supportedEfforts": ["none", "low", "medium", "high"],
        "thinkingTokenLimits": {
          "max": 38912,
          "min": 0
        }
      }
    },
    {
      "capabilities": ["reasoning", "function-call", "web-search"],
      "id": "grok-3-mini-fast-beta",
      "inputModalities": ["text"],
      "name": "Grok 3 Mini Fast Beta",
      "outputModalities": ["text"],
      "ownedBy": "xai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.33
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2.20011
        }
      },
      "reasoning": {
        "supportedEfforts": ["low", "high"]
      }
    },
    {
      "capabilities": ["function-call", "reasoning"],
      "description": "The Qwen3 series Plus model effectively integrates thinking and non-thinking modes, allowing for mode switching during conversations. Its reasoning abilities significantly surpass those of QwQ, and its general capabilities are markedly superior to Qwen2.5-Plus, reaching state-of-the-art (SOTA) levels among models of the same scale. This version is a snapshot model as of April 28, 2025.",
      "id": "qwen-plus-2025-04-28",
      "inputModalities": ["text"],
      "name": "Qwen Plus 2025 04 28",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.13
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2.6
        }
      },
      "reasoning": {
        "supportedEfforts": ["none", "low", "medium", "high"],
        "thinkingTokenLimits": {
          "max": 38912,
          "min": 0
        }
      }
    },
    {
      "capabilities": ["function-call"],
      "description": "GLM-4.1V-9B-Thinking is an open-source Vision Language Model (VLM) jointly released by Zhipu AI and the KEG Laboratory at Tsinghua University, designed specifically for handling complex multimodal cognitive tasks. Based on the GLM-4-9B-0414 foundation model, it significantly enhances cross-modal reasoning ability and stability by introducing the “Chain-of-Thought” reasoning mechanism and using reinforcement learning strategies. As a lightweight model with 9 billion parameters, it strikes a balance between deployment efficiency and performance. In 28 authoritative benchmark evaluations, it matched or even outperformed the 72-billion-parameter Qwen-2.5-VL-72B model in 18 tasks. The model excels not only in image-text understanding, mathematical and scientific reasoning, and video understanding, but also supports images up to 4K resolution and inputs of arbitrary aspect ratios.",
      "id": "glm-4-1v",
      "inputModalities": ["text"],
      "name": "Glm 4 1v",
      "outputModalities": ["text"],
      "ownedBy": "zhipu",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.04
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.16
        }
      }
    },
    {
      "capabilities": ["embedding"],
      "id": "text-embedding-004",
      "inputModalities": ["text"],
      "name": "Text Embedding 004",
      "outputModalities": ["text"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.02
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.02
        }
      }
    },
    {
      "capabilities": ["function-call", "reasoning", "image-recognition", "file-input"],
      "description": "claude code ",
      "id": "doubao-seed-code-preview-latest",
      "inputModalities": ["text"],
      "name": "Doubao Seed Code Preview Latest",
      "outputModalities": ["text"],
      "ownedBy": "bytedance",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.2
        }
      },
      "reasoning": {
        "supportedEfforts": ["none", "high"]
      },
      "contextWindow": 256000,
      "maxOutputTokens": 64000,
      "openWeights": false
    },
    {
      "capabilities": ["reasoning"],
      "description": "Simply put, it is the intelligent enhanced version of O1.",
      "id": "glm-zero-preview",
      "inputModalities": ["text"],
      "name": "Glm Zero Preview",
      "outputModalities": ["text"],
      "ownedBy": "zhipu",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      }
    },
    {
      "id": "janus-pro",
      "inputModalities": ["text"],
      "name": "Janus Pro",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      }
    },
    {
      "capabilities": ["reasoning", "function-call", "image-recognition", "web-search"],
      "description": "The Gemini 2.0 Flash Thinking mode is an experimental model designed to generate the \"thinking process\" that the model undergoes during its response. Therefore, the Gemini 2.0 Flash Thinking mode possesses stronger reasoning capabilities in its responses compared to the base Gemini 2.0 Flash model.",
      "id": "gemini-2-0-flash-thinking-exp-1219",
      "inputModalities": ["text"],
      "name": "Gemini 2 0 Flash Thinking Exp 1219",
      "outputModalities": ["text"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.076
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.304
        }
      }
    },
    {
      "capabilities": ["reasoning"],
      "id": "o1-preview-2024-09-12",
      "inputModalities": ["text"],
      "name": "O1 Preview 2024 09 12",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 7.5
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 15
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 60
        }
      },
      "reasoning": {
        "supportedEfforts": ["low", "medium", "high"]
      }
    },
    {
      "capabilities": ["reasoning"],
      "id": "qvq-preview",
      "inputModalities": ["text"],
      "name": "Qvq Preview",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 1.2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 1.2
        }
      }
    },
    {
      "capabilities": ["function-call", "structured-output", "reasoning"],
      "id": "qwq-preview",
      "inputModalities": ["text"],
      "name": "Qwq Preview",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.16
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.16
        }
      },
      "contextWindow": 131000,
      "maxOutputTokens": 131000,
      "openWeights": false,
      "family": "qwen",
      "reasoning": {
        "supportedEfforts": ["none", "auto"]
      }
    },
    {
      "capabilities": ["web-search"],
      "description": "On February 22, 2025, this model will be officially discontinued. The Perplexity AI official fine-tuned LLMA internet-connected interface is currently only supported at the api.aihubmix.com address.",
      "id": "llama-3-1-sonar-huge-128k",
      "inputModalities": ["text"],
      "name": "Llama 3 1 Sonar Huge 128k",
      "outputModalities": ["text"],
      "ownedBy": "meta",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 5.6
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 5.6
        }
      }
    },
    {
      "capabilities": ["web-search"],
      "description": "On February 22, 2025, this model will be officially discontinued; Perplexity AI's official fine-tuned LLMA internet-connected interface is currently only supported at the api.aihubmix.com address.",
      "id": "llama-3-1-sonar-large-128k",
      "inputModalities": ["text"],
      "name": "Llama 3 1 Sonar Large 128k",
      "outputModalities": ["text"],
      "ownedBy": "meta",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 1.2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 1.2
        }
      }
    },
    {
      "capabilities": ["function-call", "structured-output"],
      "contextWindow": 131072,
      "description": "This is Mistral AI's flagship model, Mistral Large 2 (version mistral-large-2407). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news/mistral-large-2407/).\n\nIt supports dozens of languages including French, German, Spanish, Italian, Portuguese, Arabic, Hindi, Russian, Chinese, Japanese, and Korean, along with 80+ coding languages including Python, Java, C, C++, JavaScript, and Bash. Its long context window allows precise information recall from large documents.\n",
      "id": "mistral-large-2407",
      "inputModalities": ["text"],
      "name": "Mistral Large 2407",
      "outputModalities": ["text"],
      "ownedBy": "mistral",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 6
        }
      },
      "maxOutputTokens": 32768,
      "openWeights": true,
      "reasoning": {
        "supportedEfforts": ["none"]
      }
    },
    {
      "capabilities": ["reasoning", "function-call", "image-recognition", "web-search"],
      "id": "gemini-2-0-flash-thinking-exp",
      "inputModalities": ["text"],
      "name": "Gemini 2 0 Flash Thinking Exp",
      "outputModalities": ["text"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.076
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.304
        }
      }
    },
    {
      "capabilities": ["image-generation"],
      "id": "gpt-image-test",
      "inputModalities": ["text"],
      "name": "GPT Image Test",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 5
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 40
        }
      }
    },
    {
      "capabilities": ["image-generation", "video-generation"],
      "description": "Imagen 3.0 is Google's latest text-to-image generation model, capable of creating high-quality images from natural language prompts. Compared to its predecessors, Imagen 3.0 offers significant improvements in detail, lighting, and reduced visual artifacts. It supports rendering in various artistic styles, from photorealism to impressionism, as well as abstract and anime styles.",
      "id": "imagen-3-0-generate-002",
      "inputModalities": ["text", "image"],
      "name": "Imagen 3 0 Generate 002",
      "outputModalities": ["image"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      }
    },
    {
      "capabilities": ["image-generation"],
      "description": "This endpoint is used to describe an image.\nSupported image formats include JPEG, PNG, and WebP.\nUS $0.01/ IMG.\nFor usage examples and pricing details, refer to the documentation at https://docs.aihubmix.com/cn/api/IdeogramAI.",
      "id": "describe",
      "inputModalities": ["text", "image"],
      "name": "Describe",
      "outputModalities": ["image"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      },
      "ownedBy": "ideogram-ai",
      "family": "ideogram-ai"
    },
    {
      "capabilities": ["image-generation"],
      "description": "The super-resolution upscale interface of the Ideogram AI drawing model is designed to enlarge low-resolution images into high-resolution ones, redrawing details (with controllable similarity and detail proportions).\nUS $0.06/ IMG.\nFor usage examples and pricing details, refer to the documentation at https://docs.aihubmix.com/cn/api/IdeogramAI.",
      "id": "upscale",
      "inputModalities": ["text", "image"],
      "name": "Upscale",
      "outputModalities": ["image"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      },
      "ownedBy": "ideogram-ai",
      "family": "ideogram-ai"
    },
    {
      "capabilities": ["computer-use"],
      "id": "computer-use-preview",
      "inputModalities": ["text"],
      "name": "Computer Use Preview",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 3
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 12
        }
      }
    },
    {
      "capabilities": ["function-call"],
      "description": "just for crush",
      "id": "crush-glm-4-6",
      "inputModalities": ["text"],
      "name": "Crush Glm 4 6",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0
        }
      }
    },
    {
      "capabilities": ["reasoning", "function-call", "image-recognition"],
      "id": "o1-2024-12-17",
      "inputModalities": ["text", "image"],
      "name": "O1 2024 12 17",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 7.5
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 15
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 60
        }
      },
      "reasoning": {
        "supportedEfforts": ["low", "medium", "high"]
      }
    },
    {
      "id": "llama2-4096",
      "inputModalities": ["text"],
      "name": "Llama2 4096",
      "outputModalities": ["text"],
      "ownedBy": "meta",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.5
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.5
        }
      }
    },
    {
      "id": "llama2-40960",
      "inputModalities": ["text"],
      "name": "Llama2 40960",
      "outputModalities": ["text"],
      "ownedBy": "meta",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.5
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.5
        }
      }
    },
    {
      "id": "llama2-2048",
      "inputModalities": ["text"],
      "name": "Llama2 2048",
      "outputModalities": ["text"],
      "ownedBy": "meta",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.1
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.1
        }
      }
    },
    {
      "id": "llama3-8192(33)",
      "inputModalities": ["text"],
      "name": "Llama3 8192(33)",
      "outputModalities": ["text"],
      "ownedBy": "meta",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2.65
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2.65
        }
      }
    },
    {
      "id": "llama3-groq-8192-tool-use-preview",
      "inputModalities": ["text"],
      "name": "Llama3 Groq 8192 Tool Use Preview",
      "outputModalities": ["text"],
      "ownedBy": "meta",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.00089
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.00089
        }
      }
    },
    {
      "id": "llama3-chat",
      "inputModalities": ["text"],
      "name": "Llama3 Chat",
      "outputModalities": ["text"],
      "ownedBy": "meta",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.3
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.3
        }
      }
    },
    {
      "capabilities": ["function-call"],
      "id": "moonshot-kimi-k2-5",
      "inputModalities": ["text"],
      "name": "Moonshot Kimi K2 5",
      "outputModalities": ["text"],
      "ownedBy": "moonshot",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.105
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.6
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 3
        }
      }
    },
    {
      "id": "moonshot-v1-128k",
      "inputModalities": ["text"],
      "name": "Moonshot V1 128k",
      "outputModalities": ["text"],
      "ownedBy": "moonshot",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 10
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 10
        }
      }
    },
    {
      "capabilities": ["image-recognition"],
      "id": "moonshot-v1-128k-vision-preview",
      "inputModalities": ["text"],
      "name": "Moonshot V1 128k Vision Preview",
      "outputModalities": ["text"],
      "ownedBy": "moonshot",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 10
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 10
        }
      }
    },
    {
      "id": "moonshot-v1-32k",
      "inputModalities": ["text"],
      "name": "Moonshot V1 32k",
      "outputModalities": ["text"],
      "ownedBy": "moonshot",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 4
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 4
        }
      }
    },
    {
      "capabilities": ["image-recognition"],
      "id": "moonshot-v1-32k-vision-preview",
      "inputModalities": ["text"],
      "name": "Moonshot V1 32k Vision Preview",
      "outputModalities": ["text"],
      "ownedBy": "moonshot",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 4
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 4
        }
      }
    },
    {
      "id": "moonshot-v1-8k",
      "inputModalities": ["text"],
      "name": "Moonshot V1 8k",
      "outputModalities": ["text"],
      "ownedBy": "moonshot",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      }
    },
    {
      "capabilities": ["image-recognition"],
      "id": "moonshot-v1-8k-vision-preview",
      "inputModalities": ["text"],
      "name": "Moonshot V1 8k Vision Preview",
      "outputModalities": ["text"],
      "ownedBy": "moonshot",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      }
    },
    {
      "capabilities": ["reasoning"],
      "id": "o1-mini-2024-09-12",
      "inputModalities": ["text"],
      "name": "O1 Mini 2024 09 12",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 1.5
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 3
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 12
        }
      },
      "reasoning": {
        "supportedEfforts": ["low", "medium", "high"]
      }
    },
    {
      "id": "omni-moderation-latest",
      "inputModalities": ["text"],
      "name": "Omni Moderation Latest",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.02
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.02
        }
      }
    },
    {
      "capabilities": ["function-call", "reasoning"],
      "description": "The model adopts tiered pricing.",
      "id": "qwen-flash-2025-07-28",
      "inputModalities": ["text"],
      "name": "Qwen Flash 2025 07 28",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.02
        },
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.02
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.2
        }
      },
      "reasoning": {
        "supportedEfforts": ["none", "low", "medium", "high"],
        "thinkingTokenLimits": {
          "max": 81920,
          "min": 0
        }
      }
    },
    {
      "capabilities": ["function-call"],
      "id": "qwen-max-longcontext",
      "inputModalities": ["text"],
      "name": "Qwen Max Longcontext",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 7
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 21
        }
      }
    },
    {
      "capabilities": ["function-call", "reasoning"],
      "id": "qwen-turbo-2024-11-01",
      "inputModalities": ["text"],
      "name": "Qwen Turbo 2024 11 01",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.36
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 1.08
        }
      },
      "reasoning": {
        "supportedEfforts": ["none", "low", "medium", "high"],
        "thinkingTokenLimits": {
          "max": 38912,
          "min": 0
        }
      }
    },
    {
      "id": "text-ada-001",
      "inputModalities": ["text"],
      "name": "Text Ada 001",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.4
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.4
        }
      }
    },
    {
      "id": "text-babbage-001",
      "inputModalities": ["text"],
      "name": "Text Babbage 001",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.5
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.5
        }
      }
    },
    {
      "id": "text-curie-001",
      "inputModalities": ["text"],
      "name": "Text Curie 001",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 2
        }
      }
    },
    {
      "id": "text-davinci-002",
      "inputModalities": ["text"],
      "name": "Text Davinci 002",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 20
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 20
        }
      }
    },
    {
      "id": "text-davinci-003",
      "inputModalities": ["text"],
      "name": "Text Davinci 003",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 20
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 20
        }
      }
    },
    {
      "id": "text-davinci-edit-001",
      "inputModalities": ["text"],
      "name": "Text Davinci Edit 001",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 20
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 20
        }
      }
    },
    {
      "capabilities": ["embedding"],
      "id": "text-embedding-v1",
      "inputModalities": ["text"],
      "name": "Text Embedding V1",
      "outputModalities": ["text"],
      "ownedBy": "alibaba",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.1
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.1
        }
      }
    },
    {
      "id": "text-moderation-007",
      "inputModalities": ["text"],
      "name": "Text Moderation 007",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.2
        }
      }
    },
    {
      "id": "text-moderation-latest",
      "inputModalities": ["text"],
      "name": "Text Moderation Latest",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.2
        }
      }
    },
    {
      "id": "text-moderation-stable",
      "inputModalities": ["text"],
      "name": "Text Moderation Stable",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.2
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 0.2
        }
      }
    },
    {
      "capabilities": ["web-search"],
      "id": "text-search-ada-doc-001",
      "inputModalities": ["text"],
      "name": "Text Search Ada Doc 001",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 20
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 20
        }
      }
    },
    {
      "capabilities": ["audio-generation"],
      "id": "tts-1",
      "inputModalities": ["audio"],
      "name": "TTS 1",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 15
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 15
        }
      }
    },
    {
      "capabilities": ["audio-generation"],
      "id": "tts-1-1106",
      "inputModalities": ["audio"],
      "name": "TTS 1 1106",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 15
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 15
        }
      }
    },
    {
      "capabilities": ["audio-generation"],
      "id": "tts-1-hd",
      "inputModalities": ["audio"],
      "name": "TTS 1 Hd",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 30
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 30
        }
      }
    },
    {
      "capabilities": ["audio-generation"],
      "id": "tts-1-hd-1106",
      "inputModalities": ["audio"],
      "name": "TTS 1 Hd 1106",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 30
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 30
        }
      }
    },
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      "capabilities": ["video-generation"],
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      "maxOutputTokens": 16384,
      "name": "OpenAI: GPT-4o-mini (2024-07-18)",
      "outputModalities": ["text"],
      "ownedBy": "openai",
      "pricing": {
        "cacheRead": {
          "currency": "USD",
          "perMillionTokens": 0.075
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        "input": {
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      "openWeights": false,
      "reasoning": {
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    },
    {
      "capabilities": ["image-generation"],
      "description": "Google's latest raw image model",
      "id": "imagen-4-0-generate-preview-05-20",
      "inputModalities": ["text", "image"],
      "name": "Imagen 4 0 Generate Preview 05 20",
      "outputModalities": ["image"],
      "ownedBy": "google",
      "pricing": {
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          "perMillionTokens": 2
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        "output": {
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    {
      "capabilities": ["embedding"],
      "description": "Model optimized for code and document search, 768-dimensional, 137M parameters.",
      "id": "jina-embeddings-v2-base-code",
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      "name": "Jina Embeddings V2 Base Code",
      "outputModalities": ["text"],
      "ownedBy": "jina",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.05
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        "output": {
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    },
    {
      "id": "learnlm-1-5-pro-experimental",
      "inputModalities": ["text"],
      "name": "Learnlm 1 5 Pro Experimental",
      "outputModalities": ["text"],
      "ownedBy": "google",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 1.25
        },
        "output": {
          "currency": "USD",
          "perMillionTokens": 5
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    },
    {
      "id": "llama-3-1-versatile",
      "inputModalities": ["text"],
      "name": "Llama 3 1 Versatile",
      "outputModalities": ["text"],
      "ownedBy": "meta",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.6
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        "output": {
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      }
    },
    {
      "capabilities": ["web-search"],
      "description": "On February 22, 2025, this model will be officially discontinued. The Perplexity AI official fine-tuned LLMA online interface is currently supported only at the api.aihubmix.com address.",
      "id": "llama-3-1-sonar-small-128k",
      "inputModalities": ["text"],
      "name": "Llama 3 1 Sonar Small 128k",
      "outputModalities": ["text"],
      "ownedBy": "meta",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.3
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      "description": "Uncensored and creative writing model based on Mistral Small 3.2 24B with good recall, prompt adherence, and intelligence.",
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      "description": "Tongyi DeepResearch is an agentic large language model developed by Tongyi Lab, with 30 billion total parameters activating only 3 billion per token. It's optimized for long-horizon, deep information-seeking tasks and delivers state-of-the-art performance on benchmarks like Humanity's Last Exam, BrowserComp, BrowserComp-ZH, WebWalkerQA, GAIA, xbench-DeepSearch, and FRAMES. This makes it superior for complex agentic search, reasoning, and multi-step problem-solving compared to prior models.\n\nThe model includes a fully automated synthetic data pipeline for scalable pre-training, fine-tuning, and reinforcement learning. It uses large-scale continual pre-training on diverse agentic data to boost reasoning and stay fresh. It also features end-to-end on-policy RL with a customized Group Relative Policy Optimization, including token-level gradients and negative sample filtering for stable training. The model supports ReAct for core ability checks and an IterResearch-based 'Heavy' mode for max performance through test-time scaling. It's ideal for advanced research agents, tool use, and heavy inference workflows.",
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      "description": "Jamba Large 1.7 is the latest model in the Jamba open family, offering improvements in grounding, instruction-following, and overall efficiency. Built on a hybrid SSM-Transformer architecture with a 256K context window, it delivers more accurate, contextually grounded responses and better steerability than previous versions.",
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      "description": "Spotlight is a 7‑billion‑parameter vision‑language model derived from Qwen 2.5‑VL and fine‑tuned by Arcee AI for tight image‑text grounding tasks. It offers a 32 k‑token context window, enabling rich multimodal conversations that combine lengthy documents with one or more images. Training emphasized fast inference on consumer GPUs while retaining strong captioning, visual‐question‑answering, and diagram‑analysis accuracy. As a result, Spotlight slots neatly into agent workflows where screenshots, charts or UI mock‑ups need to be interpreted on the fly. Early benchmarks show it matching or out‑scoring larger VLMs such as LLaVA‑1.6 13 B on popular VQA and POPE alignment tests. ",
      "id": "spotlight",
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      "name": "Arcee AI: Spotlight",
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      "description": "Maestro Reasoning is Arcee's flagship analysis model: a 32 B‑parameter derivative of Qwen 2.5‑32 B tuned with DPO and chain‑of‑thought RL for step‑by‑step logic. Compared to the earlier 7 B preview, the production 32 B release widens the context window to 128 k tokens and doubles pass‑rate on MATH and GSM‑8K, while also lifting code completion accuracy. Its instruction style encourages structured \"thought → answer\" traces that can be parsed or hidden according to user preference. That transparency pairs well with audit‑focused industries like finance or healthcare where seeing the reasoning path matters. In Arcee Conductor, Maestro is automatically selected for complex, multi‑constraint queries that smaller SLMs bounce. ",
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      "inputModalities": ["text"],
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      "name": "Arcee AI: Maestro Reasoning",
      "outputModalities": ["text"],
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      "description": "Virtuoso‑Large is Arcee's top‑tier general‑purpose LLM at 72 B parameters, tuned to tackle cross‑domain reasoning, creative writing and enterprise QA. Unlike many 70 B peers, it retains the 128 k context inherited from Qwen 2.5, letting it ingest books, codebases or financial filings wholesale. Training blended DeepSeek R1 distillation, multi‑epoch supervised fine‑tuning and a final DPO/RLHF alignment stage, yielding strong performance on BIG‑Bench‑Hard, GSM‑8K and long‑context Needle‑In‑Haystack tests. Enterprises use Virtuoso‑Large as the \"fallback\" brain in Conductor pipelines when other SLMs flag low confidence. Despite its size, aggressive KV‑cache optimizations keep first‑token latency in the low‑second range on 8× H100 nodes, making it a practical production‑grade powerhouse.",
      "id": "virtuoso-large",
      "inputModalities": ["text"],
      "maxOutputTokens": 64000,
      "name": "Arcee AI: Virtuoso Large",
      "outputModalities": ["text"],
      "ownedBy": "arceeai",
      "pricing": {
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          "perMillionTokens": 0.75
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      "openWeights": true,
      "reasoning": {
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      }
    },
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      "description": "Coder‑Large is a 32 B‑parameter offspring of Qwen 2.5‑Instruct that has been further trained on permissively‑licensed GitHub, CodeSearchNet and synthetic bug‑fix corpora. It supports a 32k context window, enabling multi‑file refactoring or long diff review in a single call, and understands 30‑plus programming languages with special attention to TypeScript, Go and Terraform. Internal benchmarks show 5–8 pt gains over CodeLlama‑34 B‑Python on HumanEval and competitive BugFix scores thanks to a reinforcement pass that rewards compilable output. The model emits structured explanations alongside code blocks by default, making it suitable for educational tooling as well as production copilot scenarios. Cost‑wise, Together AI prices it well below proprietary incumbents, so teams can scale interactive coding without runaway spend. ",
      "id": "coder-large",
      "inputModalities": ["text"],
      "name": "Arcee AI: Coder Large",
      "outputModalities": ["text"],
      "ownedBy": "arceeai",
      "pricing": {
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          "perMillionTokens": 0.5
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    },
    {
      "capabilities": [
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      "id": "llemma_7b",
      "inputModalities": ["text"],
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      "description": "This is [Sao10K](/sao10k)'s experiment over [Euryale v2.2](/sao10k/l3.1-euryale-70b).",
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      "description": "Amazon Nova Lite 1.0 is a very low-cost multimodal model from Amazon that focused on fast processing of image, video, and text inputs to generate text output. Amazon Nova Lite can handle real-time customer interactions, document analysis, and visual question-answering tasks with high accuracy.\n\nWith an input context of 300K tokens, it can analyze multiple images or up to 30 minutes of video in a single input.",
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          "perMillionTokens": 0.035
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      "capabilities": ["function-call", "structured-output", "image-recognition", "file-input"],
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      "description": "Pixtral Large is a 124B parameter, open-weight, multimodal model built on top of [Mistral Large 2](/mistralai/mistral-large-2411). The model is able to understand documents, charts and natural images.\n\nThe model is available under the Mistral Research License (MRL) for research and educational use, and the Mistral Commercial License for experimentation, testing, and production for commercial purposes.\n\n",
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      "name": "Mistral: Pixtral Large 2411",
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      "description": "SorcererLM is an advanced RP and storytelling model, built as a Low-rank 16-bit LoRA fine-tuned on [WizardLM-2 8x22B](/microsoft/wizardlm-2-8x22b).\n\n- Advanced reasoning and emotional intelligence for engaging and immersive interactions\n- Vivid writing capabilities enriched with spatial and contextual awareness\n- Enhanced narrative depth, promoting creative and dynamic storytelling",
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      "name": "SorcererLM 8x22B",
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      "name": "TheDrummer: UnslopNemo 12B",
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      "maxOutputTokens": 2048,
      "name": "Magnum v4 72B",
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        "output": {
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      "description": "Inflection 3 Pi powers Inflection's [Pi](https://pi.ai) chatbot, including backstory, emotional intelligence, productivity, and safety. It has access to recent news, and excels in scenarios like customer support and roleplay.\n\nPi has been trained to mirror your tone and style, if you use more emojis, so will Pi! Try experimenting with various prompts and conversation styles.",
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      "maxOutputTokens": 1024,
      "name": "Inflection: Inflection 3 Pi",
      "outputModalities": ["text"],
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          "perMillionTokens": 2.5
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        "output": {
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      "contextWindow": 8000,
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      "inputModalities": ["text"],
      "maxOutputTokens": 1024,
      "name": "Inflection: Inflection 3 Productivity",
      "outputModalities": ["text"],
      "ownedBy": "inflection",
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      "description": "Rocinante 12B is designed for engaging storytelling and rich prose.\n\nEarly testers have reported:\n- Expanded vocabulary with unique and expressive word choices\n- Enhanced creativity for vivid narratives\n- Adventure-filled and captivating stories",
      "id": "rocinante",
      "inputModalities": ["text"],
      "maxOutputTokens": 32768,
      "name": "TheDrummer: Rocinante 12B",
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          "perMillionTokens": 0.16999999999999998
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        "output": {
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          "perMillionTokens": 0.43
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      "contextWindow": 32768,
      "description": "Lumimaid v0.2 8B is a finetune of [Llama 3.1 8B](/models/meta-llama/llama-3.1-8b-instruct) with a \"HUGE step up dataset wise\" compared to Lumimaid v0.1. Sloppy chats output were purged.\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).",
      "id": "llama-3-1-lumimaid",
      "inputModalities": ["text"],
      "maxOutputTokens": 4096,
      "name": "NeverSleep: Lumimaid v0.2 8B",
      "outputModalities": ["text"],
      "ownedBy": "meta",
      "pricing": {
        "input": {
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          "perMillionTokens": 0.09
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        "output": {
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    },
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      "capabilities": ["function-call", "structured-output"],
      "contextWindow": 32768,
      "description": "Euryale L3.1 70B v2.2 is a model focused on creative roleplay from [Sao10k](https://ko-fi.com/sao10k). It is the successor of [Euryale L3 70B v2.1](/models/sao10k/l3-euryale-70b).",
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      "inputModalities": ["text"],
      "maxOutputTokens": 32768,
      "name": "Sao10K: Llama 3.1 Euryale 70B v2.2",
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        "output": {
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    {
      "capabilities": ["function-call"],
      "contextWindow": 8192,
      "description": "Euryale 70B v2.1 is a model focused on creative roleplay from [Sao10k](https://ko-fi.com/sao10k).\n\n- Better prompt adherence.\n- Better anatomy / spatial awareness.\n- Adapts much better to unique and custom formatting / reply formats.\n- Very creative, lots of unique swipes.\n- Is not restrictive during roleplays.",
      "id": "l3-euryale",
      "inputModalities": ["text"],
      "maxOutputTokens": 8192,
      "name": "Sao10k: Llama 3 Euryale 70B v2.1",
      "outputModalities": ["text"],
      "pricing": {
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          "perMillionTokens": 1.48
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        "output": {
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          "perMillionTokens": 1.48
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    },
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      "contextWindow": 8192,
      "description": "This safeguard model has 8B parameters and is based on the Llama 3 family. Just like is predecessor, [LlamaGuard 1](https://huggingface.co/meta-llama/LlamaGuard-7b), it can do both prompt and response classification.\n\nLlamaGuard 2 acts as a normal LLM would, generating text that indicates whether the given input/output is safe/unsafe. If deemed unsafe, it will also share the content categories violated.\n\nFor best results, please use raw prompt input or the `/completions` endpoint, instead of the chat API.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).",
      "id": "llama-guard-2",
      "inputModalities": ["text"],
      "name": "Meta: LlamaGuard 2 8B",
      "outputModalities": ["text"],
      "ownedBy": "meta",
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          "perMillionTokens": 0.19999999999999998
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          "perMillionTokens": 0.19999999999999998
        }
      }
    },
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      "contextWindow": 32768,
      "description": "A high-performing, industry-standard 7.3B parameter model, with optimizations for speed and context length.\n\nAn improved version of [Mistral 7B Instruct](/modelsmistralai/mistral-7b-instruct-v0.1), with the following changes:\n\n- 32k context window (vs 8k context in v0.1)\n- Rope-theta = 1e6\n- No Sliding-Window Attention",
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      "inputModalities": ["text"],
      "name": "Mistral: Mistral 7B Instruct v0.2",
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      "ownedBy": "mistral",
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    },
    {
      "capabilities": ["function-call", "structured-output"],
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      "description": "Mixtral 8x7B Instruct is a pretrained generative Sparse Mixture of Experts, by Mistral AI, for chat and instruction use. Incorporates 8 experts (feed-forward networks) for a total of 47 billion parameters.\n\nInstruct model fine-tuned by Mistral. #moe",
      "id": "mixtral-8x7b-instruct",
      "inputModalities": ["text"],
      "maxOutputTokens": 16384,
      "name": "Mistral: Mixtral 8x7B Instruct",
      "outputModalities": ["text"],
      "ownedBy": "mistral",
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 0.54
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        "output": {
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          "perMillionTokens": 0.54
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      },
      "openWeights": true,
      "reasoning": {
        "supportedEfforts": ["none"]
      }
    },
    {
      "capabilities": ["structured-output"],
      "contextWindow": 4096,
      "description": "A collab between IkariDev and Undi. This merge is suitable for RP, ERP, and general knowledge.\n\n#merge #uncensored",
      "id": "noromaid",
      "inputModalities": ["text"],
      "maxOutputTokens": 2048,
      "name": "Noromaid 20B",
      "outputModalities": ["text"],
      "pricing": {
        "input": {
          "currency": "USD",
          "perMillionTokens": 1
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        "output": {
          "currency": "USD",
          "perMillionTokens": 1.75
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      }
    },
    {
      "capabilities": ["structured-output"],
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      "description": "Alibaba Wan 2.7 text-to-image. Higher-fidelity successor to Wan 2.6 with thinking mode support; reference: docs.aihubmix.com/cn/api/Image-Gen.",
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    {
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      "id": "qwen-plus-2024-11-25",
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    {
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      "id": "kling_multi_elements_add",
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    {
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    {
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      "id": "vidu-get",
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    {
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      "id": "wan2-6-get",
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      "ownedBy": "dmxapi"
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      "id": "gpt-5-2-pro-responses",
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    {
      "id": "mj_turbo_shorten",
      "name": "mj_turbo_shorten",
      "ownedBy": "dmxapi"
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      "id": "somark",
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      "ownedBy": "dmxapi"
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    {
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    {
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      "id": "baichuan-m2-plus",
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      "id": "qwen-coder-plus-2024-11-06",
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      "id": "kling_lip_sync",
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    {
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    {
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    {
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      "id": "gpt-image-1-dmx01",
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    {
      "capabilities": ["video-generation"],
      "id": "mj_relax_video",
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    {
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      "ownedBy": "dmxapi"
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    {
      "id": "mj_fast_imagine",
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    {
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      "id": "kling_extend",
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      "id": "paiwo-picture",
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    {
      "id": "mj_relax_blend",
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    {
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      "id": "glm-4-0520",
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      "id": "clo-45",
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    {
      "id": "cls45-0929",
      "name": "cls45-0929",
      "ownedBy": "dmxapi"
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    {
      "id": "mj_relax_background_eraser",
      "name": "mj_relax_background_eraser",
      "ownedBy": "dmxapi"
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    {
      "id": "mj_relax_high_variation",
      "name": "mj_relax_high_variation",
      "ownedBy": "dmxapi"
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    {
      "capabilities": ["function-call"],
      "id": "doubao-seededit-3-0-i2i-250628",
      "name": "doubao-seededit-3-0-i2i-250628",
      "ownedBy": "bytedance"
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    {
      "id": "mj_fast_prompt_analyzer_extended",
      "name": "mj_fast_prompt_analyzer_extended",
      "ownedBy": "dmxapi"
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    {
      "capabilities": ["function-call"],
      "id": "qwen-coder-turbo-2024-09-19",
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    {
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      "id": "viduq2-pro",
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      "ownedBy": "vidu"
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    {
      "id": "paiwo-v5-6-ttv",
      "name": "paiwo-v5-6-ttv",
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    },
    {
      "capabilities": ["video-generation"],
      "id": "kling_multi_elements_init",
      "name": "kling_multi_elements_init",
      "ownedBy": "kling"
    },
    {
      "id": "clh45-20251001",
      "name": "clh45-20251001",
      "ownedBy": "dmxapi"
    },
    {
      "capabilities": ["video-generation"],
      "id": "do-sd-wan",
      "name": "do-sd-wan",
      "ownedBy": "dmxapi"
    },
    {
      "capabilities": ["function-call", "reasoning"],
      "id": "qwen-plus-2024-12-20",
      "name": "qwen-plus-2024-12-20",
      "ownedBy": "alibaba",
      "reasoning": {
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        "thinkingTokenLimits": {
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    },
    {
      "id": "speech-2-5-hd-preview",
      "name": "speech-2-5-hd-preview",
      "ownedBy": "dmxapi"
    },
    {
      "capabilities": ["image-recognition"],
      "id": "yi-vision",
      "name": "yi-vision",
      "ownedBy": "01ai"
    },
    {
      "id": "mj_fast_upload",
      "name": "mj_fast_upload",
      "ownedBy": "dmxapi"
    },
    {
      "capabilities": ["web-search"],
      "id": "grok-imagine-0-9",
      "name": "grok-imagine-0-9",
      "ownedBy": "xai"
    },
    {
      "id": "mj_fast_background_eraser",
      "name": "mj_fast_background_eraser",
      "ownedBy": "dmxapi"
    },
    {
      "capabilities": ["function-call", "image-recognition"],
      "id": "qwen-vl-max-2024-02-01",
      "name": "qwen-vl-max-2024-02-01",
      "ownedBy": "alibaba"
    },
    {
      "capabilities": ["image-generation"],
      "id": "imagen4",
      "name": "imagen4",
      "ownedBy": "google"
    },
    {
      "id": "mj_relax_variation",
      "name": "mj_relax_variation",
      "ownedBy": "dmxapi"
    },
    {
      "capabilities": ["audio-generation"],
      "id": "tts-pro",
      "name": "tts-pro",
      "ownedBy": "openai"
    },
    {
      "capabilities": ["function-call", "reasoning"],
      "id": "qwen-plus-2024-08-06",
      "name": "qwen-plus-2024-08-06",
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      "capabilities": ["image-recognition", "image-generation"],
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      "inputModalities": ["text"],
      "name": "即梦文生图 3.1",
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      "capabilities": ["image-generation"],
      "description": "文字响应准确度、图文排版、层次美感和语义理解能力显著提升。",
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      "name": "即梦文生图 3.0",
      "outputModalities": ["image"],
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      "family": "jimeng"
    },
    {
      "capabilities": ["image-generation"],
      "description": "高质量、富有情感和故事性的图片生成。",
      "id": "hunyuan-image-3",
      "inputModalities": ["text"],
      "name": "Hunyuan Image 3",
      "outputModalities": ["image"],
      "ownedBy": "tencent",
      "family": "hunyuan"
    },
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      "description": "擅长创建带有本地文本的图形海报。",
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      "name": "Qwen-Image 文生图",
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      "ownedBy": "alibaba",
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      "description": "支持文生图、单图生图、多图生图，以及组图生成功能。",
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      "inputModalities": ["text", "image"],
      "name": "Seedream 5.0 Lite",
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      "ownedBy": "bytedance",
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      "description": "支持4K分辨率的图像生成。",
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      "description": "The highest fidelity image model from Black Forest Labs",
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      "description": "A 12 billion parameter rectified flow transformer capable of generating images from text descriptions",
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      "id": "black-forest-labs/flux-dev",
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      "description": "Professional inpainting and outpainting model with state-of-the-art performance. Edit or extend images with natural, seamless results.",
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      "capabilities": ["image-generation"],
      "description": "Open-weight version of FLUX.1 Kontext",
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      "capabilities": ["image-generation"],
      "description": "A premium text-based image editing model that delivers maximum performance and improved typography generation for transforming images through natural language prompts",
      "family": "black-forest-labs",
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      "description": "A state-of-the-art text-based image editing model that delivers high-quality outputs with excellent prompt following and consistent results for transforming images through natural language",
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      "ownedBy": "black-forest-labs"
    },
    {
      "capabilities": ["image-generation"],
      "description": "State-of-the-art image generation with top of the line prompt following, visual quality, image detail and output diversity.",
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      "outputModalities": ["image"],
      "ownedBy": "black-forest-labs"
    },
    {
      "capabilities": ["image-generation"],
      "description": "The fastest image generation model tailored for local development and personal use",
      "family": "black-forest-labs",
      "id": "black-forest-labs/flux-schnell",
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      "name": "flux-schnell",
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      "ownedBy": "black-forest-labs"
    },
    {
      "capabilities": ["image-generation"],
      "description": "SOTA Object removal, enables precise removal of unwanted objects from images while maintaining high-quality outputs. Trained exclusively on licensed data for safe and risk-free commercial use",
      "family": "bria",
      "id": "bria/eraser",
      "inputModalities": ["text"],
      "name": "eraser",
      "outputModalities": ["image"],
      "ownedBy": "bria"
    },
    {
      "capabilities": ["image-generation"],
      "description": "Bria Expand expands images beyond their borders in high quality. Resizing the image by generating new pixels to expand to the desired aspect ratio. Trained exclusively on licensed data for safe and risk-free commercial use",
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