Cursor releases Composer 2.5 with high-performance, low-cost coding
💡New coding model hits top-tier performance at 1/10th the cost—a major win for developer productivity and budget.
⚡ 30-Second TL;DR
What Changed
Composer 2.5 achieves top-tier performance at 10% of the cost
Why It Matters
This release significantly lowers the barrier for high-quality AI-assisted coding, potentially disrupting the pricing models of existing coding agent providers.
What To Do Next
Benchmark Composer 2.5 against your current coding agent workflow to see if you can reduce API costs without sacrificing quality.
Key Points
- •Composer 2.5 achieves top-tier performance at 10% of the cost
- •Ranked 3rd in Artificial Analysis coding agent benchmarks
- •Competes directly with Claude Opus 4.7 and GPT-5.5
🧠 Deep Insight
Web-grounded analysis with 16 cited sources.
🔑 Enhanced Key Takeaways
- •Composer 2.5, released on May 18, 2026, is built upon Moonshot's open-source Kimi K2.5 checkpoint, with Cursor contributing approximately 85% of the total compute through its own additional training and reinforcement learning.
- •The model is offered in two variants: a standard version priced at $0.50 per million input tokens and $2.50 per million output tokens, and a 'Fast' variant, which is the default in Cursor, costing $3.00 per million input tokens and $15.00 per million output tokens.
- •Composer 2.5 demonstrates substantial performance improvements over its predecessor, Composer 2, achieving a 14-point increase on the Artificial Analysis Coding Agent Index (from 48 to 62) and notable gains on other benchmarks like SWE-Bench Pro (+35 points).
- •The training regimen for Composer 2.5 involved 25 times more synthetic tasks than Composer 2, incorporating targeted textual feedback for reinforcement learning to refine specific behaviors such as tool use, communication style, and effort calibration.
- •Despite its advanced capabilities, Composer 2.5 is positioned as significantly more cost-effective, with its standard variant costing as little as $0.07 per task and the Fast variant $0.44 per task, making it 10-60 times cheaper than higher-effort versions of Claude Opus 4.7 and GPT-5.5 on the Artificial Analysis Coding Agent Index.
📊 Competitor Analysis▸ Show
| Feature/Metric | Cursor Composer 2.5 | Claude Opus 4.7 | GPT-5.5 |
|---|---|---|---|
| Release Date | May 18, 2026 | April 16, 2026 | April 23, 2026 |
| Artificial Analysis Coding Agent Index | 62 | 66 (max variant in Claude Code) | 65 (xhigh reasoning in Codex) |
| SWE-Bench Multilingual / Verified | 79.8% (SWE-Bench Multilingual) | 87.6% (SWE-bench Verified) | 58.6% (SWE-Bench Pro) |
| CursorBench v3.1 | 63.2% | 70% | N/A |
| Terminal-Bench 2.0 | Improved (+2 points over Composer 2) | 69.4% | 82.7% |
| Pricing (Input/Output per 1M tokens) | Standard: $0.50 / $2.50 Fast: $3.00 / $15.00 | Standard: $5.00 / $25.00 Fast: $30.00 / $150.00 | Standard: $5.00 / $30.00 Pro: $30.00 / $180.00 |
| Cost per Task (Artificial Analysis) | Standard: $0.07 Fast: $0.44 | $4.10 (max variant in Claude Code) | $4.82 (xhigh reasoning in Codex) |
| Context Window | N/A | 1M tokens | 1M tokens, 1.1M tokens |
| Tokenizer Impact | N/A | New tokenizer may increase token counts by up to 35% for the same text | More token-efficient than GPT-5.4 |
| Availability | Exclusively in Cursor IDE and Cursor CLI (no external API) | Claude products, Anthropic API, Amazon Bedrock, Google Cloud Vertex AI, Microsoft Foundry | ChatGPT Plus, Pro, Business, Enterprise subscriptions; API access |
🛠️ Technical Deep Dive
- Composer 2.5 is built on Moonshot's open-source Kimi K2.5 checkpoint.
- Cursor reports that approximately 85% of the total compute for Composer 2.5 came from its own additional training and reinforcement learning.
- The model was trained on 25 times more synthetic tasks compared to its predecessor, Composer 2.
- A key aspect of its training involves targeted textual feedback for reinforcement learning, which helps to precisely shape specific behaviors such as tool use, communication style, and effort calibration.
- Composer 2.5 is specifically tuned for long-horizon tasks, which involve multi-step, context-heavy workflows.
🔮 Future ImplicationsAI analysis grounded in cited sources
⏳ Timeline
📎 Sources (16)
Factual claims are grounded in the sources below. Forward-looking analysis is AI-generated interpretation.
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Original source: ITmedia AI+ (日本) ↗