QwQ 32B vs Mistral Medium 3

It is close. Our weighted score puts them within a point (QwQ 32B 53/100, Mistral Medium 3 53/100), so choose by what matters most for your work: QwQ 32B for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

QwQ 32B is cheaper at $0.66 input / $1.00 output per million tokens (median across 1 API provider). Mistral Medium 3 costs $0.40 input / $2.00 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.745 per million tokens for QwQ 32B versus $0.80 for Mistral Medium 3 (1.1× as much).

QwQ 32B scores higher on the Capabilities Index (ECI): QwQ 32B 137.6 (#109 of 148) and Mistral Medium 3 134.1 (#117 of 148). The confidence ranges of the top two overlap (133.1–141.7 vs 130.5–135.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — QwQ 32B 65.3%, Mistral Medium 3 59.5%; OTIS Mock AIME 2024–2025 — QwQ 32B 59.2%, Mistral Medium 3 32.2%.

There are no published SWE-bench Verified results for QwQ 32B and Mistral Medium 3 yet, so there is no like-for-like coding score. On overall capability, QwQ 32B leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

QwQ 32B and Mistral Medium 3 share the same 131,072-token context window. Maximum output per response: QwQ 32B up to 8,192, Mistral Medium 3 up to 131,072 tokens.

QwQ 32B accepts text; Mistral Medium 3 accepts text and images. Mistral Medium 3 handles the widest range of inputs.

QwQ 32B publishes its weights and can be self-hosted; Mistral Medium 3 is proprietary.

Mistral Medium 3 is the newest, released May 7, 2025. QwQ 32B came out Mar 5, 2025. Knowledge cutoff: QwQ 32B Apr 2024, Mistral Medium 3 May 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.