docs: update MiniMax banner to M3 release

- Replace minimax-en.jpeg and minimax-zh.jpeg with new M3 PNG banners
- Update MiniMax description in both READMEs to reflect M3 benchmarks
  (SWE-Bench Pro 59.0, Terminal Bench 2.1 66.0, VIBE V2 60.1, etc.)
- Update tagline: "Build, Learn & Ship" / "Mini 价格 Max 性能"

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

README.md

@@ -47,9 +47,9 @@
 <details open>
 <summary>Sponsors</summary>
 
-[![MiniMax](assets/banners/minimax-en.jpeg)](https://platform.minimax.io/subscribe/token-plan?code=lqYrKBvjke&source=link)
+[![MiniMax](assets/banners/minimax-en.png)](https://platform.minimax.io/subscribe/token-plan?code=lqYrKBvjke&source=link)
 
-MiniMax-M2.7 is a next-generation large language model designed for autonomous evolution and real-world productivity. Unlike traditional models, M2.7 actively participates in its own improvement through agent teams, dynamic tool use, and reinforcement learning loops. It delivers strong performance in software engineering (56.22% on SWE-Pro, 55.6% on VIBE-Pro, 57.0% on Terminal Bench 2) and excels in complex office workflows, achieving a leading 1495 ELO on GDPval-AA. With high-fidelity editing across Word, Excel, and PowerPoint, and a 97% adherence rate across 40+ complex skills, M2.7 sets a new standard for building AI-native workflows and organizations.
+MiniMax-M3 pushes the frontier of coding and agentic AI, with a 1M-token context window powered by MiniMax Sparse Attention and natively multimodal capabilities from step zero. It leads across SWE-Bench Pro (59.0), Terminal Bench 2.1 (66.0), VIBE V2 (60.1), SVG-Bench (63.7), KernelBench Hard (28.8), BrowseComp (83.5), GDPval rubrics (74.7), Banker ToolBench (76.1), MCP Atlas (74.2), and OSWorld-verified (70.0). Build, learn, and ship with the MiniMax Token Plan.
 
 [Click here](https://platform.minimax.io/subscribe/token-plan?code=lqYrKBvjke&source=link) to get an exclusive 12% off the MiniMax Token Plan + voucher for cc-connect users!
 

README.zh-CN.md

@@ -47,9 +47,9 @@
 <details open>
 <summary>赞助商</summary>
 
-[![MiniMax](assets/banners/minimax-zh.jpeg)](https://platform.minimaxi.com/subscribe/token-plan?code=HAvthxk1tT&source=link)
+[![MiniMax](assets/banners/minimax-zh.png)](https://platform.minimaxi.com/subscribe/token-plan?code=HAvthxk1tT&source=link)
 
-MiniMax M2.7 是 MiniMax 首个深度参与自我迭代的模型，可自主构建复杂 Agent Harness，并基于 Agent Teams、复杂 Skills、Tool Search Tool 等能力完成高复杂度生产力任务；其在软件工程、端到端项目交付及办公场景中表现优异，多项评测接近行业领先水平，同时具备稳定的复杂任务执行、环境交互能力以及良好的情商与身份保持能力。
+MiniMax M3 突破 Coding 与 Agentic AI 前沿，基于 MiniMax Sparse Attention 支持 1M 超长上下文，并从零原生支持多模态。在 SWE-Bench Pro (59.0)、Terminal Bench 2.1 (66.0)、VIBE V2 (60.1)、SVG-Bench (63.7)、KernelBench Hard (28.8)、BrowseComp (83.5)、GDPval rubrics (74.7)、Banker ToolBench (76.1)、MCP Atlas (74.2)、OSWorld-verified (70.0) 等多项基准中领先业界。Mini 价格 Max 性能，Token Plan 助你 Build / Learn / Ship。
 
 [点击此处](https://platform.minimaxi.com/subscribe/token-plan?code=HAvthxk1tT&source=link)享 MiniMax Token Plan 专属 88 折优惠 + cc-connect 用户专属代金券！