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. | 7B | 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 | Feb 5 2024 | May 29 2024 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
DeepSeek-MathvsClaude Haiku 5.5Codestral 22BvsClaude Haiku 5.5DeepSeek-MathvsGPT-6.1 SolCodestral 22BvsGPT-6.1 SolDeepSeek-MathvsGemini 4 ArgonCodestral 22BvsGemini 4 ArgonDeepSeek-MathvsMuse Spark OpenCodestral 22BvsMuse Spark OpenDeepSeek-MathvsGrok 4.7Codestral 22BvsGrok 4.7DeepSeek-MathvsKimi K3Codestral 22BvsKimi K3Frequently asked questions
DeepSeek-Math and Codestral 22B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-Math shipped 114 days before Codestral 22B, so benchmark comparisons should account for the intervening progress.
DeepSeek-Math has 7B parameters, while Codestral 22B has 22B. Context windows are 4k (DeepSeek-Math) vs 32k (Codestral 22B). DeepSeek-Math is open weight, while Codestral 22B is closed.
Direct benchmark comparisons are unavailable — DeepSeek-Math and Codestral 22B don't publish scores on any of the same benchmarks.