GPT-4.1 nano vs Qwen3 30B A3B vs Gemma 3 27B IT

It is close. Our weighted score puts them within 2 points (GPT-4.1 nano 63/100, Gemma 3 27B IT 60/100, Qwen3 30B A3B 58/100), so choose by what matters most for your work: Qwen3 30B A3B for raw capability, Gemma 3 27B IT on price and GPT-4.1 nano for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Gemma 3 27B IT is cheaper at $0.08 input / $0.20 output per million tokens (median across 9 API providers). GPT-4.1 nano costs $0.10 input / $0.40 output per million tokens (official OpenAI API price); Qwen3 30B A3B costs $0.114 input / $0.50 output per million tokens (median across 8 API providers). At a typical mix of three input tokens to one output token, that is $0.11 per million tokens for Gemma 3 27B IT versus $0.175 for GPT-4.1 nano (1.6× as much) and $0.21 for Qwen3 30B A3B (1.9× as much).

Qwen3 30B A3B scores higher on the Capabilities Index (ECI): Qwen3 30B A3B 136.2 (#112 of 148), Gemma 3 27B IT 130.0 (#125 of 148) and GPT-4.1 nano 129.6 (#127 of 148). The confidence ranges of the top two overlap (130.3–138.7 vs 124.1–132.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3 30B A3B 61.7%, GPT-4.1 nano 48.9%, Gemma 3 27B IT 47.7%; OTIS Mock AIME 2024–2025 — Qwen3 30B A3B 62.8%, GPT-4.1 nano 28.9%, Gemma 3 27B IT 22.5%.

There are no published SWE-bench Verified results for GPT-4.1 nano, Qwen3 30B A3B and Gemma 3 27B IT yet, so there is no like-for-like coding score. On overall capability, Qwen3 30B A3B leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

GPT-4.1 nano has the largest context window at 1,047,576 tokens, against 131,072 for Qwen3 30B A3B and 131,072 for Gemma 3 27B IT. Maximum output per response: GPT-4.1 nano up to 32,768, Qwen3 30B A3B up to 16,384, Gemma 3 27B IT up to 131,072 tokens.

GPT-4.1 nano accepts text and images; Qwen3 30B A3B accepts text; Gemma 3 27B IT accepts text and images. GPT-4.1 nano handles the widest range of inputs.

Qwen3 30B A3B and Gemma 3 27B IT publishes its weights and can be self-hosted; GPT-4.1 nano is proprietary.

Qwen3 30B A3B is the newest, released Apr 28, 2025. GPT-4.1 nano came out Apr 14, 2025; Gemma 3 27B IT came out Mar 12, 2025. Knowledge cutoff: GPT-4.1 nano Apr 2024, Gemma 3 27B IT Aug 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.