Gemma 3 12B IT vs Mistral Large

Gemma 3 12B IT is the better all-round choice, scoring 57/100 against Mistral Large (44). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Gemma 3 12B IT is cheaper at $0.05 input / $0.15 output per million tokens (median across 12 API providers). 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 $0.075 per million tokens for Gemma 3 12B IT versus $0.75 for Mistral Large (10× as much).

Gemma 3 12B IT scores higher on the Capabilities Index (ECI): Gemma 3 12B IT 123.5 (#151 of 165) and Mistral Large 122.0 (#153 of 165). The confidence ranges of the top two overlap (116.9–128.4 vs 115.7–124.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Gemma 3 12B IT 39.5%, Mistral Large 38.8%; OTIS Mock AIME 2024–2025 — Gemma 3 12B IT 16.7%, Mistral Large 1.9%.

There are no published SWE-bench Verified results for Gemma 3 12B IT and Mistral Large yet, so there is no like-for-like coding score. On overall capability, Gemma 3 12B IT leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Gemma 3 12B IT has the largest context window at 131,072 tokens, against 128,000 for Mistral Large. Maximum output per response: Gemma 3 12B IT up to 131,072, Mistral Large up to 102,400 tokens.

Gemma 3 12B IT accepts text and images; Mistral Large accepts text and PDFs. They handle the same number of input types.

Gemma 3 12B IT publishes its weights and can be self-hosted; Mistral Large is proprietary.

Gemma 3 12B IT is the newest, released Mar 12, 2025. Mistral Large came out Feb 26, 2024. Knowledge cutoff: Gemma 3 12B IT Aug 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.