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 | 1T |
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 | 256k |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | — | $0.60Google |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $2.50Google |
| — | $245Novita · bf16 | |
| These models have no shared benchmark scores. | ||
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | — | 71.3% |
| Overview | ||
| Company | Mistral | Moonshot AI |
| Release date | Jul 16 2024 | Nov 6 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
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Codestral Mamba 7B and Kimi K2 Thinking don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Codestral Mamba 7B shipped 478 days before Kimi K2 Thinking, so benchmark comparisons should account for the intervening progress.
Codestral Mamba 7B has 7B parameters, while Kimi K2 Thinking has 1T. Context windows are 256k (Codestral Mamba 7B) vs 256k (Kimi K2 Thinking).
Direct benchmark comparisons are unavailable — Codestral Mamba 7B and Kimi K2 Thinking don't publish scores on any of the same benchmarks.