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. | — | 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. | 256k | 1M |
| Overview | ||
| Company | Mistral | Moonshot AI |
| Release date | Jan 13 2025 | Oct 30 2025 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Codestral 25.01vsClaude Haiku 5.5Kimi LinearvsClaude Haiku 5.5Codestral 25.01vsGPT-6.1 SolKimi LinearvsGPT-6.1 SolCodestral 25.01vsGemini 4 ArgonKimi LinearvsGemini 4 ArgonCodestral 25.01vsMuse Spark OpenKimi LinearvsMuse Spark OpenCodestral 25.01vsGrok 4.7Kimi LinearvsGrok 4.7Codestral 25.01vsDeepSeek-V4.1-Flash-1017Kimi LinearvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Codestral 25.01 and Kimi Linear don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Codestral 25.01 shipped 290 days before Kimi Linear, so benchmark comparisons should account for the intervening progress.
Context windows are 256k (Codestral 25.01) vs 1M (Kimi Linear). Codestral 25.01 is closed, while Kimi Linear is open weight.
Direct benchmark comparisons are unavailable — Codestral 25.01 and Kimi Linear don't publish scores on any of the same benchmarks.