Qwen2.5 32B Instruct vs Ministral 8B Instruct

It is close. Our weighted score puts them within 1 points (Ministral 8B Instruct 42/100, Qwen2.5 32B Instruct 41/100), so choose by what matters most for your work: Qwen2.5 32B Instruct for raw capability and Ministral 8B Instruct on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because Ministral 8B Instruct has no Capabilities Index score yet.

Ministral 8B Instruct is cheaper at $0.15 input / $0.15 output per million tokens (median across 1 API provider). Qwen2.5 32B Instruct costs $0.70 input / $2.80 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Ministral 8B Instruct versus $1.23 for Qwen2.5 32B Instruct (8.2× as much).

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond): Qwen2.5 32B Instruct 46.1% and Ministral 8B Instruct 27.2%. On individual benchmarks: GPQA Diamond — Qwen2.5 32B Instruct 46.1%, Ministral 8B Instruct 27.2%.

There are no published SWE-bench Verified results for Qwen2.5 32B Instruct and Ministral 8B Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 32B Instruct leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Qwen2.5 32B Instruct and Ministral 8B Instruct share the same 131,072-token context window. Maximum output per response: Qwen2.5 32B Instruct up to 8,192, Ministral 8B Instruct up to 8,192 tokens.

Qwen2.5 32B Instruct accepts text; Ministral 8B Instruct accepts text. They handle the same number of input types.

Yes, both publish their weights (Mistral Research License), so you can self-host them.

Ministral 8B Instruct is the newest, released Oct 16, 2024. Qwen2.5 32B Instruct came out Sep 17, 2024. Knowledge cutoff: Qwen2.5 32B Instruct Apr 2024.

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.