Compare AI models
| Specifications | ||
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 400k | — |
| Benchmarks | ||
Next.js EvalsNext.js coding — Vercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | 46% | 82% |
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 45% | — |
SWE-Bench ProAgentic coding — Can the AI fix real bugs in real software? It's handed actual problems from open-source projects and has to write code that genuinely solves them. Higher is better. | — | 54% |
SWE-Bench MultilingualMultilingual coding — Like SWE-Bench, but the coding problems span many programming languages, not just one. Tests how broadly the AI can code. Higher is better. | — | 79.8% |
CursorBench 4.0Agentic coding — Cursor's own test of coding agents on ambiguous, multi-file tasks taken from real Cursor sessions — editing, refactoring, investigating a codebase, understanding what the user meant, managing jobs and following a design. Cursor runs each model at several reasoning efforts; each release here carries the score of its best listed effort. Scores aren't comparable with earlier CursorBench versions. Higher is better. | — | 27.7% |
DeepSWE 1.0Agentic coding — Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. Higher is better. | — | 18% |
Terminal-Bench 2.1Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | — | 73% |
Terminal-Bench 2.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? (Version 2.0 of the test.) Higher is better. | — | 69.3% |
threejsevalCommunity preference (Three.js) — Every model gets the same prompt — "the Eiffel Tower", "a glass fishbowl", "a robot arm picking toys into a box" — and builds a 3D scene in Three.js. Real people then see two scenes side by side, names hidden, and vote for the one they prefer. The votes become a chess-style Elo rating on threejseval.com, averaged across all the prompts. It measures whether the scene looks and moves right to a human eye, not whether the code passes a test. Higher is better. | — | 1083 |
| Overview | ||
| Company | OpenAI | SpaceXSI |
| Release date | Dec 18 2025 | May 18 2026 |
| Access | Closed | Closed |
| Model details | View model | View model |
Other comparisons
GPT-5.2-CodexvsClaude Fable 5.2Composer 2.5vsClaude Fable 5.2GPT-5.2-CodexvsGemini 4 CarbonComposer 2.5vsGemini 4 CarbonGPT-5.2-CodexvsMuse EmberComposer 2.5vsMuse EmberGPT-5.2-CodexvsDeepSeek-V4.1-Flash-1017Composer 2.5vsDeepSeek-V4.1-Flash-1017GPT-5.2-CodexvsMistral Large 4Composer 2.5vsMistral Large 4GPT-5.2-CodexvsKimi K3.1 ProComposer 2.5vsKimi K3.1 ProFrequently asked questions
Composer 2.5 leads GPT-5.2-Codex on 1 of the 1 benchmark they both report (Next.js Evals). GPT-5.2-Codex shipped 151 days before Composer 2.5, so benchmark comparisons should account for the intervening progress.
Published specifications for these two models are limited — see each model page for the latest details.
On Next.js Evals, Composer 2.5 leads at 82% vs GPT-5.2-Codex at 46%.