Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | 24B | — |
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. | 256k | 400k |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | — | $1.25Azure |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $10.00Azure |
| — | $750Azure | |
| These models have no shared benchmark scores. | ||
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 68% | — |
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. | 55.7% | — |
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. | 22.5% | — |
| Overview | ||
| Company | Mistral | OpenAI |
| Release date | Dec 9 2025 | Nov 19 2025 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
Devstral Small 2 (24B)vsClaude Haiku 5.5GPT-5.1-Codex-MaxvsClaude Haiku 5.5Devstral Small 2 (24B)vsGemini 4 ArgonGPT-5.1-Codex-MaxvsGemini 4 ArgonDevstral Small 2 (24B)vsMuse Spark OpenGPT-5.1-Codex-MaxvsMuse Spark OpenDevstral Small 2 (24B)vsGrok 4.7GPT-5.1-Codex-MaxvsGrok 4.7Devstral Small 2 (24B)vsDeepSeek-V4.1-Flash-1017GPT-5.1-Codex-MaxvsDeepSeek-V4.1-Flash-1017Devstral Small 2 (24B)vsKimi K3GPT-5.1-Codex-MaxvsKimi K3Frequently asked questions
Devstral Small 2 (24B) and GPT-5.1-Codex-Max don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. GPT-5.1-Codex-Max shipped 20 days before Devstral Small 2 (24B), so benchmark comparisons should account for the intervening progress.
Context windows are 256k (Devstral Small 2 (24B)) vs 400k (GPT-5.1-Codex-Max). Devstral Small 2 (24B) is open weight, while GPT-5.1-Codex-Max is closed.
Direct benchmark comparisons are unavailable — Devstral Small 2 (24B) and GPT-5.1-Codex-Max don't publish scores on any of the same benchmarks.