Mistral Medium 3.5vsGPT-6 Sol
Mistral Medium 3.5 | GPT-6 Sol | |
|---|---|---|
| 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 | 1.05M |
| API pricingUSD per 1M tokens · lower wins · base tier | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $1.50 | $2.00 |
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 | $10.00 |
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. | — | $0.20 |
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. | $1.50Mistral | — |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $7.50Mistral | — |
| 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% | — |
DeepSWE 1.1Agentic coding — Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. (Version 1.1 of the test.) Higher is better. | — | 68.8% |
OSWorld 2.0Agentic computer use — Can the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Version 2.0 is a harder, refreshed task set. Higher is better. | — | 60.5% |
Agent's Last Exam · pass@1Agentic computer use — A hard set of desktop and operating-system tasks an AI agent has to finish by looking at the screen and working the machine itself. The score is the share it passes outright — partial credit does not count. Higher is better. | — | 56.4% |
AutomationBenchBusiness workflows — Tests whether the AI can run real multi-step business workflows — the kind of end-to-end office processes companies want to automate — from start to finish. Higher is better. | — | 33.2% |
| Overview | ||
| Company | Mistral | OpenAI |
| Release date | Apr 29 2026 | Sep 22 2026 |
| Access | Open Weight | Proprietary |
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Frequently asked questions
Mistral Medium 3.5 and GPT-6 Sol 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 $2.00 per million input tokens, and $7.50 vs $10.00 per million output tokens. Figures are base-tier rates. Mistral Medium 3.5 shipped 146 days before GPT-6 Sol, so benchmark comparisons should account for the intervening progress.
Context windows are 256k (Mistral Medium 3.5) vs 1.05M (GPT-6 Sol). Mistral Medium 3.5 is open weight, while GPT-6 Sol is proprietary.
Direct benchmark comparisons are unavailable — Mistral Medium 3.5 and GPT-6 Sol don't publish scores on any of the same benchmarks.