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. | 236B | 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. | 128k | 256k |
| 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 | DeepSeek | Mistral |
| Release date | Sep 5 2024 | Dec 9 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
DeepSeek V2.5vsClaude Haiku 5.5Devstral Small 2 (24B)vsClaude Haiku 5.5DeepSeek V2.5vsGPT-6.1 SolDevstral Small 2 (24B)vsGPT-6.1 SolDeepSeek V2.5vsGemini 4 ArgonDevstral Small 2 (24B)vsGemini 4 ArgonDeepSeek V2.5vsMuse Spark OpenDevstral Small 2 (24B)vsMuse Spark OpenDeepSeek V2.5vsGrok 4.7Devstral Small 2 (24B)vsGrok 4.7DeepSeek V2.5vsKimi K3Devstral Small 2 (24B)vsKimi K3Frequently asked questions
DeepSeek V2.5 and Devstral Small 2 (24B) don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek V2.5 shipped 460 days before Devstral Small 2 (24B), so benchmark comparisons should account for the intervening progress.
DeepSeek V2.5 has 236B parameters, while Devstral Small 2 (24B) has 24B. Context windows are 128k (DeepSeek V2.5) vs 256k (Devstral Small 2 (24B)).
Direct benchmark comparisons are unavailable — DeepSeek V2.5 and Devstral Small 2 (24B) don't publish scores on any of the same benchmarks.