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. | 1.8B/3.25B | 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. | 32k | 32k |
| Overview | ||
| Company | Mistral | |
| Release date | Dec 6 2023 | May 29 2024 |
| Access | Closed | Closed |
| Model details | View model | View model |
Other comparisons
Gemini 1.0 NanovsClaude Haiku 5.5Codestral 22BvsClaude Haiku 5.5Gemini 1.0 NanovsGPT-6.1 SolCodestral 22BvsGPT-6.1 SolGemini 1.0 NanovsMuse Spark OpenCodestral 22BvsMuse Spark OpenGemini 1.0 NanovsGrok 4.7Codestral 22BvsGrok 4.7Gemini 1.0 NanovsDeepSeek-V4.1-Flash-1017Codestral 22BvsDeepSeek-V4.1-Flash-1017Gemini 1.0 NanovsKimi K3Codestral 22BvsKimi K3Frequently asked questions
Gemini 1.0 Nano and Codestral 22B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Gemini 1.0 Nano shipped 175 days before Codestral 22B, so benchmark comparisons should account for the intervening progress.
Gemini 1.0 Nano has 1.8B/3.25B parameters, while Codestral 22B has 22B. Context windows are 32k (Gemini 1.0 Nano) vs 32k (Codestral 22B).
Direct benchmark comparisons are unavailable — Gemini 1.0 Nano and Codestral 22B don't publish scores on any of the same benchmarks.