GPT-5.4 nano vs Qwen3.6 27B vs MiniMax-M2.7

It is close. Our weighted score puts them within 3 points (GPT-5.4 nano 68/100, Qwen3.6 27B 65/100, MiniMax-M2.7 61/100), so choose by what matters most for your work: Qwen3.6 27B for raw capability, GPT-5.4 nano on price and GPT-5.4 nano for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

GPT-5.4 nano is cheaper at $0.20 input / $1.25 output per million tokens (official OpenAI API price). MiniMax-M2.7 costs $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price); Qwen3.6 27B costs $0.60 input / $3.60 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.463 per million tokens for GPT-5.4 nano versus $0.525 for MiniMax-M2.7 (1.1× as much) and $1.35 for Qwen3.6 27B (2.9× as much).

Qwen3.6 27B scores higher on the Capabilities Index (ECI): Qwen3.6 27B 146.5 (#68 of 148), MiniMax-M2.7 145.9 (#73 of 148) and GPT-5.4 nano 145.8 (#75 of 148). The confidence ranges of the top two overlap (144.2–147.9 vs 138.2–148.0), so treat the gap as small.

There are no published SWE-bench Verified results for GPT-5.4 nano, Qwen3.6 27B and MiniMax-M2.7 yet, so there is no like-for-like coding score. On overall capability, Qwen3.6 27B leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

GPT-5.4 nano has the largest context window at 400,000 tokens, against 262,144 for Qwen3.6 27B and 204,800 for MiniMax-M2.7. Maximum output per response: GPT-5.4 nano up to 128,000, Qwen3.6 27B up to 65,536, MiniMax-M2.7 up to 131,072 tokens.

GPT-5.4 nano accepts text and images; Qwen3.6 27B accepts text, images, audio and video; MiniMax-M2.7 accepts text. Qwen3.6 27B handles the widest range of inputs.

Qwen3.6 27B and MiniMax-M2.7 publishes its weights and can be self-hosted; GPT-5.4 nano is proprietary.

Qwen3.6 27B is the newest, released Apr 22, 2026. MiniMax-M2.7 came out Mar 18, 2026; GPT-5.4 nano came out Mar 17, 2026. Knowledge cutoff: GPT-5.4 nano Aug 31, 2025.

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.