GPT-5.4 nano vs Qwen3 8B vs MiniMax-M2.7

GPT-5.4 nano is the better all-round choice, scoring 68/100 against MiniMax-M2.7 (61) and Qwen3 8B (56). It leads on inputs & features and context window. Qwen3 8B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Qwen3 8B is cheaper at $0.18 input / $0.70 output per million tokens (official Alibaba API price). GPT-5.4 nano costs $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). At a typical mix of three input tokens to one output token, that is $0.31 per million tokens for Qwen3 8B versus $0.463 for GPT-5.4 nano (1.5× as much) and $0.525 for MiniMax-M2.7 (1.7× as much).

MiniMax-M2.7 scores higher on the Capabilities Index (ECI): MiniMax-M2.7 145.9 (#73 of 148), GPT-5.4 nano 145.8 (#75 of 148) and Qwen3 8B 136.2 (#113 of 148). The confidence ranges of the top two overlap (138.2–148.0 vs 143.2–147.7), so treat the gap as small.

There are no published SWE-bench Verified results for GPT-5.4 nano, Qwen3 8B and MiniMax-M2.7 yet, so there is no like-for-like coding score. On overall capability, MiniMax-M2.7 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 204,800 for MiniMax-M2.7 and 131,072 for Qwen3 8B. Maximum output per response: GPT-5.4 nano up to 128,000, Qwen3 8B up to 8,192, MiniMax-M2.7 up to 131,072 tokens.

GPT-5.4 nano accepts text and images; Qwen3 8B accepts text; MiniMax-M2.7 accepts text. GPT-5.4 nano handles the widest range of inputs.

Qwen3 8B and MiniMax-M2.7 publishes its weights and can be self-hosted; GPT-5.4 nano is proprietary.

MiniMax-M2.7 is the newest, released Mar 18, 2026. GPT-5.4 nano came out Mar 17, 2026; Qwen3 8B came out Apr 28, 2025. Knowledge cutoff: GPT-5.4 nano Aug 31, 2025, Qwen3 8B Apr 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.