Gemma 2 27B vs Aya Expanse 32B vs Mistral Large

Mistral Large is the better all-round choice, scoring 45/100 against Aya Expanse 32B (32) and Gemma 2 27B (28). It leads on inputs & features. Gemma 2 27B wins on price. 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.

Gemma 2 27B is cheaper at $0.65 input / $0.65 output per million tokens (median across 3 API providers). Aya Expanse 32B costs $0.50 input / $1.50 output per million tokens (official Cohere API price); Mistral Large costs $0.50 input / $1.50 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.65 per million tokens for Gemma 2 27B versus $0.75 for Aya Expanse 32B (1.2× as much) and $0.75 for Mistral Large (1.2× as much).

There is no independent benchmark that covers all three models yet. Gemma 2 27B has an ECI of 122.1, Aya Expanse 32B has not been scored yet and Mistral Large has an ECI of 122.0.

There are no published SWE-bench Verified results for Gemma 2 27B, Aya Expanse 32B and Mistral Large yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Gemma 2 27B and Aya Expanse 32B does not support tool calling, which most coding agents need.

Aya Expanse 32B and Mistral Large have the largest context windows (128,000 and 128,000 tokens), against 8,192 for Gemma 2 27B. Maximum output per response: Gemma 2 27B up to 2,048, Aya Expanse 32B up to 4,000, Mistral Large up to 102,400 tokens.

Gemma 2 27B accepts text; Aya Expanse 32B accepts text; Mistral Large accepts text and PDFs. Mistral Large handles the widest range of inputs.

Gemma 2 27B and Aya Expanse 32B publishes its weights (CC-BY-NC-4.0) and can be self-hosted; Mistral Large is proprietary.

Aya Expanse 32B is the newest, released Oct 24, 2024. Gemma 2 27B came out Jul 13, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Gemma 2 27B Jun 30, 2024, 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.