Mistral Medium 3.5vsQwen3.5-Plus
Mistral Medium 3.5 | Qwen3.5-Plus | |
|---|---|---|
| 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 | 1M |
| 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 | $0.40 |
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 | $2.40 |
| 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 | Feb 16 2026 |
| Access | Open Weight | Proprietary |
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Frequently asked questions
Mistral Medium 3.5 and Qwen3.5-Plus don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen3.5-Plus is cheaper on both input and output: $0.40 vs $1.50 per million input tokens, and $2.40 vs $7.50 per million output tokens. Figures are base-tier rates. Qwen3.5-Plus shipped 72 days before Mistral Medium 3.5, so benchmark comparisons should account for the intervening progress.
Context windows are 256k (Mistral Medium 3.5) vs 1M (Qwen3.5-Plus). Mistral Medium 3.5 is open weight, while Qwen3.5-Plus is proprietary.
Direct benchmark comparisons are unavailable — Mistral Medium 3.5 and Qwen3.5-Plus don't publish scores on any of the same benchmarks.