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Model Drop

Composer 2

Composer 2
Composer 2

Composer 2, which Cursor shipped on March 19, 2026, is Cursor's second-generation coding model, built by further training Moonshot AI's open Kimi K2.5 for long agentic coding tasks.

  • Model: Composer 2 (composer-2)

  • Maker: Cursor

  • Ship date: March 19, 2026

  • Pricing: $0.50 / $2.50 per M tokens (Fast: $1.50 / $7.50)

  • Context: 200K tokens

  • Where you can use it:

    • Cursor, with the Fast variant as default

    • The early alpha of Cursor's new interface

  • When to reach for it:

    • Everyday agent coding on a budget

    • Long, many-step tasks inside Cursor

    • Skip it for the toughest terminal work

  • How it compares:

    • Near GPT-5.4 for a fraction of the price

    • Edges Claude Opus 4.6 on Cursor's tests

  • What makes it different:

    • Cursor's first continued pretraining run

    • Self-summarizes to keep long tasks going

  • Early reactions: The low price drew attention, but the launch was clouded when a user found it was built on Kimi K2.5, which Cursor admitted it should've disclosed.

  • Read more: Introducing Composer 2, Composer 2 Technical Report

The benchmarks

Cursor ran Composer models in its own harness, ran Claude Opus 4.6 and 4.5 at high effort (GPT-5.4 at high on CursorBench), and reported rivals from its harness (SWE-bench Multilingual) or the best of the official leaderboard and its own runs (Terminal-Bench 2.0); Anthropic's self-reported Terminal-Bench 2.0 score for Claude Opus 4.6 (65.4%) is higher than the 58.0% Cursor used.

Cursor's numbers

  • CursorBench (Cursor's internal coding eval, v3): 61.3%. +2.2 over GPT-5.3-Codex (59.1%), +3.1 over Claude Opus 4.6 (58.2%), +25.3 over Kimi K2.5 (36.0%), −2.6 under GPT-5.4 (63.9%).

  • Terminal-Bench 2.0 (command-line agent tasks): 61.7%. +3.7 over Claude Opus 4.6 (58.0%), +9.6 over Claude Opus 4.5 (52.1%), −13.4 under GPT-5.4 (75.1%).

  • SWE-bench Multilingual (GitHub fixes, many languages): 73.7%. +8.6 over Kimi K2.5 (65.1%), −2.1 under Claude Opus 4.6 (75.8%), −3.1 under GPT-5.4 (76.8%).

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