Artificial Analysis@ArtificialAnlys

2026-05-21 09:48·43天前

AI 摘要

Cursor发布了其编程智能体模型Composer 2.5，在Artificial Analysis编程智能体指数中排名第三，仅次于Claude Opus 4.7和GPT-5.5。该模型的核心优势在于极高的性价比：其标准版任务成本仅为0.07美元，比顶级竞品便宜约60倍。性能方面，它在SWE-Bench-Pro-Hard-AA等基准测试上较前代有显著提升。模型基于月之暗面的Kimi K2.5开源权重进行训练，目前仅限在Cursor产品内使用，未提供独立API。

Cursor's new Composer 2.5 takes third on the Artificial Analysis Coding Agent Index and is ~10-60x lower cost than the higher-effort Opus 4.7 and GPT-5.5 variants above it. This release puts Composer among the leading coding agent models， something that wasn't clear for past releases

@cursor_ai has released Composer 2.5， the latest model in its Composer line. Composer 2.5 scored 62 on our Coding Agent Index， a 14 point gain over Composer 2 （48）. This puts it in third place of our tested agents， behind only Claude Opus 4.7 （max） in Claude Code （66） and GPT-5.5 （xhigh reasoning） in Codex （65）. These cost $4.10 and $4.82 per task respectively， ~10x the cost of Composer 2.5 Fast （$0.44） and ~60x the cost of Composer 2.5 standard （$0.07）.

Key results for Composer 2.5 in Cursor CLI：

➤ Cost-quality Pareto frontier： At $0.07 （standard） and $0.44 （Fast） per task， Composer 2.5 is cheaper than every other agent scoring above 60 on the Index. Medium-effort peers cost $1.24-$2.21 per task； higher-effort variants land 3-4 points above at $4.10-$4.82

➤ Per-benchmark gains vs Composer 2： +35 points on SWE-Bench-Pro-Hard-AA （12% → 47%）， +2 points on Terminal-Bench v2 （64% → 66%）， and +3 points on SWE-Atlas-QnA （69% → 72%）. At 47%， Composer 2.5's score on SWE-Bench-Pro-Hard-AA is comparable to Claude Opus 4.7 （max） in Claude Code

➤ Among the fastest coding agents： Composer 2.5 Fast runs at an average wall time of 6.7 minutes per task， the third-fastest agent on the Artificial Analysis Coding Agent Index， behind only Claude Opus 4.7 （medium） in Claude Code （5.8m） and GPT-5.5 （medium） in Cursor CLI （6.2m）

➤ Fast mode enables better responsiveness at 6x pricing： Fast runs 30% faster than standard Composer 2.5， but is ~6x the cost per task （$0.44 vs $0.07）. Token pricing is 6x higher for Fast： $3.00/$15.00 vs $0.50/$2.50 per million input/output tokens

Model details：

➤ Base model： Continued training on @Kimi_Moonshot's open weights Kimi K2.5 as with Composer 2， with Cursor reporting ~85% of total compute from its own additional training and reinforcement learning

Artificial Analysis@ArtificialAnlys · X

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2026-05-21 09:48·43天前

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AI 摘要