On May 18, Cursor released its third-generation in-house coding model, Composer 2.5. The core numbers are striking: 79.8% on SWE-Bench Multilingual, essentially on par with Claude Opus 4.7 and GPT-5.5; on the SWE-Bench-Pro-Hard-AA subset — the most challenging slice for top-tier models — Composer 2.5 jumped 35 percentage points over its predecessor. Even more noteworthy is the price: $0.50 per million input tokens and $2.50 per million output tokens on the standard tier — roughly one-tenth of top closed-source models. What does that mean? The economics of coding AI are being rewritten. Previously, only Anthropic and OpenAI's flagships had models above 75% on SWE-Bench, and the steep inference cost forced many teams to choose between "good" and "affordable." Composer 2.5 hits the same accuracy at one-tenth the cost — a big deal for long-running AI coding agents.
On the technical side, Composer 2.5 is built on Moonshot's Kimi K2.5. Cursor revealed that 85% of its compute budget went into post-training and reinforcement learning on top of the base, with 25× more synthetic task data than the previous generation. This "stand on the shoulders of open source and apply large-scale targeted tuning" approach is becoming the mainstream playbook for small-to-mid labs competing against the giants.
The release of Composer 2.5 marks the formal entry of the AI coding-agent market into a price-performance competition — no longer just "whose score is highest." The question now is: with the cost of entry-level coding agents dropping to one-tenth, how much pressure will that put on the pricing strategies of traditional IDE plugins and the Copilots? The ultimate winners of this price war are the developers.