GPT-5.4 nano vs Qwen3.6 Max Preview

GPT-5.4 nano is the better all-round choice, scoring 68/100 against Qwen3.6 Max Preview (54). It leads on price, inputs & features and context window. Qwen3.6 Max Preview wins on capability. 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). Qwen3.6 Max Preview costs $1.30 input / $7.80 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 $2.92 for Qwen3.6 Max Preview (6.3× as much).

Qwen3.6 Max Preview scores higher on the Capabilities Index (ECI): Qwen3.6 Max Preview 149.2 (#54 of 148) and GPT-5.4 nano 145.8 (#75 of 148). The confidence ranges of the top two overlap (147.6–152.0 vs 143.2–147.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.6 Max Preview 87.4%, GPT-5.4 nano 78.5%; OTIS Mock AIME 2024–2025 — Qwen3.6 Max Preview 91.1%, GPT-5.4 nano 87.8%; SimpleQA Verified — Qwen3.6 Max Preview 52.0%, GPT-5.4 nano 11.7%.

There are no published SWE-bench Verified results for GPT-5.4 nano yet, so there is no like-for-like coding score. On overall capability, Qwen3.6 Max Preview leads, which tends to carry over to coding, but test on your own codebase. Both 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 Max Preview. Maximum output per response: GPT-5.4 nano up to 128,000, Qwen3.6 Max Preview up to 65,536 tokens.

GPT-5.4 nano accepts text and images; Qwen3.6 Max Preview accepts text. GPT-5.4 nano handles the widest range of inputs.

No. GPT-5.4 nano and Qwen3.6 Max Preview are proprietary and only available through APIs and apps.

Qwen3.6 Max Preview is the newest, released Apr 20, 2026. GPT-5.4 nano came out Mar 17, 2026. Knowledge cutoff: GPT-5.4 nano Aug 31, 2025, Qwen3.6 Max Preview 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.