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. | 124B | 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. | 128k | 1M |
| Overview | ||
| Company | Mistral | Moonshot AI |
| Release date | Nov 18 2024 | Oct 30 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Pixtral Large 24.11vsClaude Haiku 5.5Kimi LinearvsClaude Haiku 5.5Pixtral Large 24.11vsGPT-6.1 SolKimi LinearvsGPT-6.1 SolPixtral Large 24.11vsGemini 4 ArgonKimi LinearvsGemini 4 ArgonPixtral Large 24.11vsMuse Spark OpenKimi LinearvsMuse Spark OpenPixtral Large 24.11vsGrok 4.7Kimi LinearvsGrok 4.7Pixtral Large 24.11vsDeepSeek-V4.1-Flash-1017Kimi LinearvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Pixtral Large 24.11 and Kimi Linear don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Pixtral Large 24.11 shipped 346 days before Kimi Linear, so benchmark comparisons should account for the intervening progress.
Pixtral Large 24.11 has 124B parameters, while Kimi Linear has 48B. Context windows are 128k (Pixtral Large 24.11) vs 1M (Kimi Linear).
Direct benchmark comparisons are unavailable — Pixtral Large 24.11 and Kimi Linear don't publish scores on any of the same benchmarks.