Mistral Medium 3.5vso1
Mistral Medium 3.5 | o1 | |
|---|---|---|
| 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. | 128B | — |
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 | 200k |
| 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. | $1.50 | $15.00 |
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. | $7.50 | $60.00 |
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. | — | $7.50 |
| BenchmarksPublished by one model only | ||
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. | 77.6% | — |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 75.7% |
| Overview | ||
| Company | Mistral | OpenAI |
| Release date | Apr 29 2026 | Dec 5 2024 |
| Access | Open Weight | Proprietary |
Other comparisons
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Frequently asked questions
Mistral Medium 3.5 and o1 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral Medium 3.5 is cheaper on both input and output: $1.50 vs $15.00 per million input tokens, and $7.50 vs $60.00 per million output tokens. o1 shipped 510 days before Mistral Medium 3.5, so benchmark comparisons should account for the intervening progress.
Context windows are 256k (Mistral Medium 3.5) vs 200k (o1). Mistral Medium 3.5 is open weight, while o1 is proprietary.
Direct benchmark comparisons are unavailable — Mistral Medium 3.5 and o1 don't publish scores on any of the same benchmarks.