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 | 7B |
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 | 256k |
| Overview | ||
| Company | Mistral | |
| Release date | Dec 6 2023 | Jul 16 2024 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
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Gemini 1.0 Nano and Codestral Mamba 7B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Gemini 1.0 Nano shipped 223 days before Codestral Mamba 7B, so benchmark comparisons should account for the intervening progress.
Gemini 1.0 Nano has 1.8B/3.25B parameters, while Codestral Mamba 7B has 7B. Context windows are 32k (Gemini 1.0 Nano) vs 256k (Codestral Mamba 7B). Gemini 1.0 Nano is closed, while Codestral Mamba 7B is open weight.
Direct benchmark comparisons are unavailable — Gemini 1.0 Nano and Codestral Mamba 7B don't publish scores on any of the same benchmarks.