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 | — |
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 | 400k |
| Overview | ||
| Company | Mistral | OpenAI |
| Release date | Jul 16 2024 | Nov 13 2025 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
Mathstral 7BvsClaude Fable 5.2GPT-5.1-Codex-MinivsClaude Fable 5.2Mathstral 7BvsGemini 4 CarbonGPT-5.1-Codex-MinivsGemini 4 CarbonMathstral 7BvsMuse EmberGPT-5.1-Codex-MinivsMuse EmberMathstral 7BvsGrok 4.7GPT-5.1-Codex-MinivsGrok 4.7Mathstral 7BvsDeepSeek-V4.1-Flash-1017GPT-5.1-Codex-MinivsDeepSeek-V4.1-Flash-1017Mathstral 7BvsKimi K3.1 ProGPT-5.1-Codex-MinivsKimi K3.1 ProFrequently asked questions
Mathstral 7B and GPT-5.1-Codex-Mini don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mathstral 7B shipped 485 days before GPT-5.1-Codex-Mini, so benchmark comparisons should account for the intervening progress.
Context windows are 32k (Mathstral 7B) vs 400k (GPT-5.1-Codex-Mini). Mathstral 7B is open weight, while GPT-5.1-Codex-Mini is closed.
Direct benchmark comparisons are unavailable — Mathstral 7B and GPT-5.1-Codex-Mini don't publish scores on any of the same benchmarks.