Gemma 3 4B IT vs Qwen Turbo

Qwen Turbo is the better all-round choice, scoring 48/100 against Gemma 3 4B IT (43). It leads on capability and context window. Gemma 3 4B IT wins on inputs & features. 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 4B IT is cheaper at $0.05 input / $0.10 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 $0.063 per million tokens for Gemma 3 4B IT versus $0.087 for Qwen Turbo (1.4× 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): Qwen Turbo 24.0% and Gemma 3 4B IT 15.4%. On individual benchmarks: GPQA Diamond — Qwen Turbo 41.8%, Gemma 3 4B IT 23.2%; OTIS Mock AIME 2024–2025 — Gemma 3 4B IT 7.5%, Qwen Turbo 6.1%.

There are no published SWE-bench Verified results for Gemma 3 4B IT and Qwen Turbo yet, so there is no like-for-like coding score. On overall capability, Qwen Turbo 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 4B IT. Maximum output per response: Gemma 3 4B IT up to 131,072, Qwen Turbo up to 16,384 tokens.

Gemma 3 4B IT accepts text and images; Qwen Turbo accepts text. Gemma 3 4B IT handles the widest range of inputs.

Gemma 3 4B IT publishes its weights and can be self-hosted; Qwen Turbo is proprietary.

Gemma 3 4B IT is the newest, released Mar 12, 2025. Qwen Turbo came out Nov 1, 2024. Knowledge cutoff: Gemma 3 4B 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.