Mistral Large 2.1 vs Mixtral 8x7B vs Qwen2.5 32B Instruct

Qwen2.5 32B Instruct is the better all-round choice, scoring 43/100 against Mistral Large 2.1 (38) and Mixtral 8x7B (37). Mixtral 8x7B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Mixtral 8x7B is cheaper at $0.70 input / $0.70 output per million tokens (official Mistral API price). Qwen2.5 32B Instruct costs $0.70 input / $2.80 output per million tokens (official Alibaba API price); Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.70 per million tokens for Mixtral 8x7B versus $1.23 for Qwen2.5 32B Instruct (1.8× as much) and $3.00 for Mistral Large 2.1 (4.3× as much).

Mistral Large 2.1 scores higher on the Capabilities Index (ECI): Mistral Large 2.1 128.5 (#130 of 148), Qwen2.5 32B Instruct 128.5 (#131 of 148) and Mixtral 8x7B 118.5 (#142 of 148). The confidence ranges of the top two overlap (123.8–130.8 vs 123.5–130.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Qwen2.5 32B Instruct 46.1%, Mixtral 8x7B 30.6%.

There are no published SWE-bench Verified results for Mistral Large 2.1, Mixtral 8x7B and Qwen2.5 32B Instruct yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2.1 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Mistral Large 2.1 and Qwen2.5 32B Instruct have the largest context windows (131,072 and 131,072 tokens), against 32,000 for Mixtral 8x7B. Maximum output per response: Mistral Large 2.1 up to 16,384, Mixtral 8x7B up to 32,000, Qwen2.5 32B Instruct up to 8,192 tokens.

Mistral Large 2.1 accepts text; Mixtral 8x7B accepts text; Qwen2.5 32B Instruct accepts text. They handle the same number of input types.

Yes, all three publish their weights, so you can self-host them.

Mistral Large 2.1 is the newest, released Nov 18, 2024. Qwen2.5 32B Instruct came out Sep 17, 2024; Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Mistral Large 2.1 Nov 2024, Mixtral 8x7B Jan 2024, 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.