Qwen2.5-Coder-32B-Instruct vs Mistral Large vs Aya Expanse 32B

Mistral Large is the better all-round choice, scoring 45/100 against Qwen2.5-Coder-32B-Instruct (39) and Aya Expanse 32B (32). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Qwen2.5-Coder-32B-Instruct is cheaper at $0.66 input / $1.00 output per million tokens (median across 7 API providers). Mistral Large costs $0.50 input / $1.50 output per million tokens (official Mistral API price); Aya Expanse 32B costs $0.50 input / $1.50 output per million tokens (official Cohere API price). At a typical mix of three input tokens to one output token, that is $0.745 per million tokens for Qwen2.5-Coder-32B-Instruct versus $0.75 for Mistral Large (1× as much) and $0.75 for Aya Expanse 32B (1× as much).

There is no independent benchmark that covers all three models yet. Qwen2.5-Coder-32B-Instruct has not been scored yet, Mistral Large has an ECI of 122.0 and Aya Expanse 32B has not been scored yet.

There are no published SWE-bench Verified results for Qwen2.5-Coder-32B-Instruct, Mistral Large and Aya Expanse 32B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Aya Expanse 32B does not support tool calling, which most coding agents need.

Qwen2.5-Coder-32B-Instruct has the largest context window at 131,072 tokens, against 128,000 for Mistral Large and 128,000 for Aya Expanse 32B. Maximum output per response: Qwen2.5-Coder-32B-Instruct up to 8,192, Mistral Large up to 102,400, Aya Expanse 32B up to 4,000 tokens.

Qwen2.5-Coder-32B-Instruct accepts text; Mistral Large accepts text and PDFs; Aya Expanse 32B accepts text. Mistral Large handles the widest range of inputs.

Qwen2.5-Coder-32B-Instruct and Aya Expanse 32B publishes its weights (CC-BY-NC-4.0) and can be self-hosted; Mistral Large is proprietary.

Qwen2.5-Coder-32B-Instruct is the newest, released Nov 12, 2024. Aya Expanse 32B came out Oct 24, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Mistral Large Nov 30, 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 Nov 2, 2026.