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 | May 6 2024 | Dec 11 2023 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
DeepSeek V2vsClaude Haiku 5.5Mistral MediumvsClaude Haiku 5.5DeepSeek V2vsGPT-6.1 SolMistral MediumvsGPT-6.1 SolDeepSeek V2vsGemini 4 ArgonMistral MediumvsGemini 4 ArgonDeepSeek V2vsMuse Spark OpenMistral MediumvsMuse Spark OpenDeepSeek V2vsGrok 4.7Mistral MediumvsGrok 4.7DeepSeek V2vsKimi K3Mistral MediumvsKimi K3Frequently asked questions
DeepSeek V2 and Mistral Medium don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral Medium shipped 147 days before DeepSeek V2, so benchmark comparisons should account for the intervening progress.
Context windows are 128k (DeepSeek V2) vs 32k (Mistral Medium). DeepSeek V2 is open weight, while Mistral Medium is closed.
Direct benchmark comparisons are unavailable — DeepSeek V2 and Mistral Medium don't publish scores on any of the same benchmarks.