Gemma 3 27B IT vs Qwen Turbo

Gemma 3 27B IT is the better all-round choice, scoring 51/100 against Qwen Turbo (48). It leads on capability and inputs & features. Qwen Turbo wins on price and context window. 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.

Qwen Turbo is cheaper at $0.05 input / $0.20 output per million tokens (official Alibaba API price). Gemma 3 27B IT costs $0.08 input / $0.20 output per million tokens (median across 9 API providers). At a typical mix of three input tokens to one output token, that is $0.087 per million tokens for Qwen Turbo versus $0.11 for Gemma 3 27B IT (1.3× 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 27B IT 35.1% and Qwen Turbo 24.0%. On individual benchmarks: GPQA Diamond — Gemma 3 27B IT 47.7%, Qwen Turbo 41.8%; OTIS Mock AIME 2024–2025 — Gemma 3 27B IT 22.5%, Qwen Turbo 6.1%.

There are no published SWE-bench Verified results for Gemma 3 27B IT and Qwen Turbo yet, so there is no like-for-like coding score. On overall capability, Gemma 3 27B 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 27B IT. Maximum output per response: Gemma 3 27B IT up to 131,072, Qwen Turbo up to 16,384 tokens.

Gemma 3 27B IT accepts text and images; Qwen Turbo accepts text. Gemma 3 27B IT handles the widest range of inputs.

Gemma 3 27B IT publishes its weights and can be self-hosted; Qwen Turbo is proprietary.

Gemma 3 27B IT is the newest, released Mar 12, 2025. Qwen Turbo came out Nov 1, 2024. Knowledge cutoff: Gemma 3 27B 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.