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 | 8k |
| Overview | ||
| Company | Mistral | |
| Release date | Dec 6 2023 | Sep 27 2023 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Gemini 1.0 NanovsClaude Haiku 5.5Mistral 7BvsClaude Haiku 5.5Gemini 1.0 NanovsGPT-6.1 SolMistral 7BvsGPT-6.1 SolGemini 1.0 NanovsMuse Spark OpenMistral 7BvsMuse Spark OpenGemini 1.0 NanovsGrok 4.7Mistral 7BvsGrok 4.7Gemini 1.0 NanovsDeepSeek-V4.1-Flash-1017Mistral 7BvsDeepSeek-V4.1-Flash-1017Gemini 1.0 NanovsKimi K3Mistral 7BvsKimi K3Frequently asked questions
Gemini 1.0 Nano and Mistral 7B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral 7B shipped 70 days before Gemini 1.0 Nano, so benchmark comparisons should account for the intervening progress.
Gemini 1.0 Nano has 1.8B/3.25B parameters, while Mistral 7B has 7B. Context windows are 32k (Gemini 1.0 Nano) vs 8k (Mistral 7B). Gemini 1.0 Nano is closed, while Mistral 7B is open weight.
Direct benchmark comparisons are unavailable — Gemini 1.0 Nano and Mistral 7B don't publish scores on any of the same benchmarks.