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 | — |
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 | 32k |
| Overview | ||
| Company | DeepSeek | Mistral |
| Release date | Sep 5 2024 | Feb 26 2024 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
DeepSeek V2.5vsClaude Haiku 5.5Mistral SmallvsClaude Haiku 5.5DeepSeek V2.5vsGPT-6.1 SolMistral SmallvsGPT-6.1 SolDeepSeek V2.5vsGemini 4 ArgonMistral SmallvsGemini 4 ArgonDeepSeek V2.5vsMuse Spark OpenMistral SmallvsMuse Spark OpenDeepSeek V2.5vsGrok 4.7Mistral SmallvsGrok 4.7DeepSeek V2.5vsKimi K3Mistral SmallvsKimi K3Frequently asked questions
DeepSeek V2.5 and Mistral Small don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral Small shipped 192 days before DeepSeek V2.5, so benchmark comparisons should account for the intervening progress.
Context windows are 128k (DeepSeek V2.5) vs 32k (Mistral Small). DeepSeek V2.5 is open weight, while Mistral Small is closed.
Direct benchmark comparisons are unavailable — DeepSeek V2.5 and Mistral Small don't publish scores on any of the same benchmarks.