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 | 0.5B/1.5B/3B/7B/14B/32B/72B |
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 | 128k |
| 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. | — | $0.36DeepInfra |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $0.40DeepInfra |
| — | $92.00DeepInfra · fp8 | |
| 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 | Qwen |
| Release date | Dec 9 2025 | Sep 19 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Devstral Small 2 (24B)vsClaude Haiku 5.5Qwen2.5vsClaude Haiku 5.5Devstral Small 2 (24B)vsGPT-6.1 SolQwen2.5vsGPT-6.1 SolDevstral Small 2 (24B)vsGemini 4 ArgonQwen2.5vsGemini 4 ArgonDevstral Small 2 (24B)vsMuse Spark OpenQwen2.5vsMuse Spark OpenDevstral Small 2 (24B)vsGrok 4.7Qwen2.5vsGrok 4.7Devstral Small 2 (24B)vsDeepSeek-V4.1-Flash-1017Qwen2.5vsDeepSeek-V4.1-Flash-1017Frequently asked questions
Devstral Small 2 (24B) and Qwen2.5 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen2.5 shipped 446 days before Devstral Small 2 (24B), so benchmark comparisons should account for the intervening progress.
Devstral Small 2 (24B) has 24B parameters, while Qwen2.5 has 0.5B/1.5B/3B/7B/14B/32B/72B. Context windows are 256k (Devstral Small 2 (24B)) vs 128k (Qwen2.5).
Direct benchmark comparisons are unavailable — Devstral Small 2 (24B) and Qwen2.5 don't publish scores on any of the same benchmarks.