Gemma 3 12B IT vs Qwen Turbo

It is close. Our weighted score puts them within a point (Gemma 3 12B IT 49/100, Qwen Turbo 48/100), so choose by what matters most for your work: Gemma 3 12B IT for raw capability and Qwen Turbo for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Qwen Turbo has no Capabilities Index score yet.

Gemma 3 12B IT is cheaper at $0.05 input / $0.15 output per million tokens (median across 7 API providers). Qwen Turbo costs $0.05 input / $0.20 output per million tokens (official Alibaba 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 $0.087 for Qwen Turbo (1.2× as much).

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025): Gemma 3 12B IT 28.1% and Qwen Turbo 24.0%. On individual benchmarks: GPQA Diamond — Qwen Turbo 41.8%, Gemma 3 12B IT 39.5%; OTIS Mock AIME 2024–2025 — Gemma 3 12B IT 16.7%, Qwen Turbo 6.1%.

There are no published SWE-bench Verified results for Gemma 3 12B IT and Qwen Turbo 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.

Qwen Turbo has the largest context window at 1,000,000 tokens, against 131,072 for Gemma 3 12B IT. Maximum output per response: Gemma 3 12B IT up to 131,072, Qwen Turbo up to 16,384 tokens.

Gemma 3 12B IT accepts text and images; Qwen Turbo accepts text. Gemma 3 12B IT handles the widest range of inputs.

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

Gemma 3 12B IT is the newest, released Mar 12, 2025. Qwen Turbo came out Nov 1, 2024. Knowledge cutoff: Gemma 3 12B IT Aug 2024, Qwen Turbo 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.