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 | 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. | 4k | 32k |
| Overview | ||
| Company | DeepSeek | Mistral |
| Release date | Jan 11 2024 | May 29 2024 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
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DeepSeek-MoE and Codestral 22B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-MoE shipped 139 days before Codestral 22B, so benchmark comparisons should account for the intervening progress.
DeepSeek-MoE has 16B parameters, while Codestral 22B has 22B. Context windows are 4k (DeepSeek-MoE) vs 32k (Codestral 22B). DeepSeek-MoE is open weight, while Codestral 22B is closed.
Direct benchmark comparisons are unavailable — DeepSeek-MoE and Codestral 22B don't publish scores on any of the same benchmarks.