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. | 16B/236B | 22B |
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 | Jun 17 2024 | May 29 2024 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
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DeepSeek Coder V2 and Codestral 22B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Codestral 22B shipped 19 days before DeepSeek Coder V2, so benchmark comparisons should account for the intervening progress.
DeepSeek Coder V2 has 16B/236B parameters, while Codestral 22B has 22B. Context windows are 128k (DeepSeek Coder V2) vs 32k (Codestral 22B). DeepSeek Coder V2 is open weight, while Codestral 22B is closed.
Direct benchmark comparisons are unavailable — DeepSeek Coder V2 and Codestral 22B don't publish scores on any of the same benchmarks.