Mistral Medium 3 vs Qwen3 Max

It is close. Our weighted score puts them within 3 points (Mistral Medium 3 53/100, Qwen3 Max 50/100), so choose by what matters most for your work: Qwen3 Max for raw capability and Mistral Medium 3 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Mistral Medium 3 is cheaper at $0.40 input / $2.00 output per million tokens (official Mistral API price). Qwen3 Max costs $1.20 input / $6.00 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.80 per million tokens for Mistral Medium 3 versus $2.40 for Qwen3 Max (3× as much).

Qwen3 Max scores higher on the Capabilities Index (ECI): Qwen3 Max 142.4 (#91 of 148) and Mistral Medium 3 134.1 (#117 of 148). Their confidence ranges do not overlap (140.0–144.6 vs 130.5–135.6), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen3 Max 72.6%, Mistral Medium 3 59.5%; OTIS Mock AIME 2024–2025 — Qwen3 Max 73.3%, Mistral Medium 3 32.2%.

There are no published SWE-bench Verified results for Mistral Medium 3 and Qwen3 Max yet, so there is no like-for-like coding score. On overall capability, Qwen3 Max leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Qwen3 Max has the largest context window at 262,144 tokens, against 131,072 for Mistral Medium 3. Maximum output per response: Mistral Medium 3 up to 131,072, Qwen3 Max up to 65,536 tokens.

Mistral Medium 3 accepts text and images; Qwen3 Max accepts text. Mistral Medium 3 handles the widest range of inputs.

No. Mistral Medium 3 and Qwen3 Max are proprietary and only available through APIs and apps.

Qwen3 Max is the newest, released Sep 23, 2025. Mistral Medium 3 came out May 7, 2025. Knowledge cutoff: Mistral Medium 3 May 2025, Qwen3 Max Apr 2025.

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.