Compare AI models
| Specifications | ||
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 | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | — | $1.10 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | — | $4.40 |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | — | $0.55 |
These models have no shared benchmark scores. | ||
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 60% |
| Overview | ||
| Company | Mistral | OpenAI |
| Release date | Jan 13 2025 | Sep 12 2024 |
| Access | Closed | Closed |
| Model details | View model | View model |
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Codestral 25.01 and o1-mini don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only o1-mini has a verified first-party API price: $1.10 per million input tokens and $4.40 per million output tokens. No pay-as-you-go API rate is tracked for Codestral 25.01. o1-mini shipped 123 days before Codestral 25.01, so benchmark comparisons should account for the intervening progress.
Context windows are 256k (Codestral 25.01) vs 128k (o1-mini).
Direct benchmark comparisons are unavailable — Codestral 25.01 and o1-mini don't publish scores on any of the same benchmarks.