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 | 48B |
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 | 1M |
| Overview | ||
| Company | Mistral | Moonshot AI |
| Release date | Jul 16 2024 | Oct 30 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Mathstral 7BvsClaude Haiku 5.5Kimi LinearvsClaude Haiku 5.5Mathstral 7BvsGPT-6.1 SolKimi LinearvsGPT-6.1 SolMathstral 7BvsGemini 4 ArgonKimi LinearvsGemini 4 ArgonMathstral 7BvsMuse Spark OpenKimi LinearvsMuse Spark OpenMathstral 7BvsGrok 4.7Kimi LinearvsGrok 4.7Mathstral 7BvsDeepSeek-V4.1-Flash-1017Kimi LinearvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Mathstral 7B and Kimi Linear don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mathstral 7B shipped 471 days before Kimi Linear, so benchmark comparisons should account for the intervening progress.
Mathstral 7B has 7B parameters, while Kimi Linear has 48B. Context windows are 32k (Mathstral 7B) vs 1M (Kimi Linear).
Direct benchmark comparisons are unavailable — Mathstral 7B and Kimi Linear don't publish scores on any of the same benchmarks.