Mistral Medium 3.5vsQwen3
Mistral Medium 3.5 | Qwen3 | |
|---|---|---|
| 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 | 235B |
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 · 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 | $0.70 |
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 | $2.80 |
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. | — | $0.0482StreamLake |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $0.1931StreamLake |
| 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% | — |
| Overview | ||
| Company | Mistral | Qwen |
| Release date | Apr 29 2026 | Apr 29 2025 |
| Access | Open Weight | Open Weight |
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Frequently asked questions
Mistral Medium 3.5 and Qwen3 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen3 is cheaper on both input and output: $0.70 vs $1.50 per million input tokens, and $2.80 vs $7.50 per million output tokens. Figures are base-tier rates. Qwen3 shipped 365 days before Mistral Medium 3.5, so benchmark comparisons should account for the intervening progress.
Mistral Medium 3.5 has 128B parameters, while Qwen3 has 235B. Context windows are 256k (Mistral Medium 3.5) vs 128k (Qwen3).
Direct benchmark comparisons are unavailable — Mistral Medium 3.5 and Qwen3 don't publish scores on any of the same benchmarks.