Codestral 25.01vsKimi K2
Codestral 25.01 | Kimi K2 | |
|---|---|---|
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | — | 1T |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 256k | 128k |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | — | $0.57Novita |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $2.30Novita |
| BenchmarksPublished by one model only | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | — | 10% |
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. | — | 65.8% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 75.1% |
| Overview | ||
| Company | Mistral | Moonshot AI |
| Release date | Jan 13 2025 | Jul 11 2025 |
| Access | Proprietary | Open Weight |
Other comparisons
Frequently asked questions
Codestral 25.01 and Kimi K2 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Codestral 25.01 shipped 179 days before Kimi K2, so benchmark comparisons should account for the intervening progress.
Context windows are 256k (Codestral 25.01) vs 128k (Kimi K2). Codestral 25.01 is proprietary, while Kimi K2 is open weight.
Direct benchmark comparisons are unavailable — Codestral 25.01 and Kimi K2 don't publish scores on any of the same benchmarks.
Codestral 25.01 was released by Mistral on Jan 13 2025.
Kimi K2 was released by Moonshot AI on Jul 11 2025.
Codestral 25.01 has a 256k context window; Kimi K2 has 128k.
Codestral 25.01 is a proprietary model released by Mistral. Kimi K2 is an open weight model released by Moonshot AI.