Composer 2.5 vs Qwen3.7-Max

The article discusses Cursor's release of the Composer 2.5 model, claiming it is currently the best coding model with excellent performance and cost-effectiveness.

The "smart, fast, cheap" trilemma limitation of AI models has been broken by Cursor's Composer 2.5, which can simultaneously achieve all three characteristics.

After the $10K Cursor credit expired, users reported that Agent Window mode almost completely replaced traditional IDEs; GPT-5.5 and Composer 2.5 performed well in different scenarios, especially Composer 2.5 Fast mode which is fast and good at generating flowcharts, but default output is not Markdown and cannot be copied directly as Markdown, affecting efficiency.

Cursor has released an SDK supporting Python and TypeScript for building custom AI agents using Composer 2.5, offering a 90% discount on Composer usage during a limited-time promotion.

The Cursor team achieved Composer 2.5 through reinforcement learning training rather than prompt engineering, with their large-scale RL program running inference on Fireworks, indicating that self-trained models will be the only way to maintain competitive moats after 2027.

Cursor released Composer 2.5, using Kimi as a base with 85% compute for self-training. It matches Claude Opus 4.7 performance at 1/10th the cost via targeted RL and 25x synthetic data.

The Cursor SDK now supports programmatic access to Composer 2.5's frontier intelligence features via Python and TypeScript, allowing developers to build their own AI agents with 90% discount during the long weekend.

Composer 2.5 is having a moment. Worth a look at how the team actually got here.

The U.S. government's new executive order balances AI development with security, Qwen3.7-Max enters the top three models, and AI vulnerability detection breaks copyright alignment.

ITBench-AA is a new benchmark series evaluating models on agentic enterprise IT tasks, starting with Site Reliability Engineering tasks where frontier models score below 50% on ITBench-AA's SRE tasks benchmark model performance on Kubernetes incident response, where models and agents must diagnose live systems by reading logs, tracing dependencies, and identifying root-cause entities across complex infrastructure.

Qwen3.7-Max has become the second-best AI programming model globally, scoring 1541 on Code Arena, trailing only Claude. Designed for production use, it can handle 35-hour tasks, over 1,000 tool calls, and complete two-week projects in hours.

阿里巴巴推出全新升级的超大规模语言模型 Qwen3.7-Max，该模型专为代理中心工作设计，如编码、办公和生产任务以及长期自主执行。相较于前代 Qwen3.6，Qwen3.7-Max 在编码和代理基准测试中取得了显著进步，并引入了显式提示缓存功能，以优化重复上下文的处理。

阿里巴巴推出Qwen3.7-Max，作为面向代理时代的最新旗舰模型，它是一个多功能的基础模型，适用于能够实际完成任务的代理。该模型在编码代理方面表现出色，能够进行前端原型设计、多文件重构和实际调试。此外，它还是一个可靠的办公和生产力助手。

Qwen3.7-Max在编码代理和通用代理的基准测试中表现出色，尤其在最难的推理基准上表现出色，并在通用能力和多语言支持方面脱颖而出。

Qwen3.7-Max 在人工智能分析指数上获得了56.6分，比Qwen3.6-Max-Preview提高了4.8分。它在科学推理、代理能力、编码能力和减少幻觉方面都有显著提升。

Alibaba Cloud's Qwen3.7-Max scores 56.6 to rank 5th globally and 1st domestically in Artificial Analysis benchmark, soon available via Alibaba Cloud's BaiLian API.