GPT-5 Nano vs Qwen3 235B-A22B Thinking 2507

GPT-5 Nano is the better all-round choice, scoring 68/100 against Qwen3 235B-A22B Thinking 2507 (55). It leads on price, inputs & features and context window. Qwen3 235B-A22B Thinking 2507 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

GPT-5 Nano is cheaper at $0.05 input / $0.40 output per million tokens (official OpenAI API price). Qwen3 235B-A22B Thinking 2507 costs $0.30 input / $2.90 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.138 per million tokens for GPT-5 Nano versus $0.95 for Qwen3 235B-A22B Thinking 2507 (6.9× as much).

Qwen3 235B-A22B Thinking 2507 scores higher on the Capabilities Index (ECI): Qwen3 235B-A22B Thinking 2507 143.8 (#93 of 165) and GPT-5 Nano 139.3 (#116 of 165). Their confidence ranges do not overlap (141.9–145.2 vs 134.3–141.5), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen3 235B-A22B Thinking 2507 80.1%, GPT-5 Nano 69.4%; OTIS Mock AIME 2024–2025 — Qwen3 235B-A22B Thinking 2507 86.7%, GPT-5 Nano 81.1%; SimpleQA Verified — Qwen3 235B-A22B Thinking 2507 40.4%, GPT-5 Nano 11.7%.

There are no published SWE-bench Verified results for GPT-5 Nano and Qwen3 235B-A22B Thinking 2507 yet, so there is no like-for-like coding score. On overall capability, Qwen3 235B-A22B Thinking 2507 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

GPT-5 Nano has the largest context window at 400,000 tokens, against 262,144 for Qwen3 235B-A22B Thinking 2507. Maximum output per response: GPT-5 Nano up to 128,000, Qwen3 235B-A22B Thinking 2507 up to 81,920 tokens.

GPT-5 Nano accepts text and images; Qwen3 235B-A22B Thinking 2507 accepts text. GPT-5 Nano handles the widest range of inputs.

Qwen3 235B-A22B Thinking 2507 publishes its weights (Apache 2.0) and can be self-hosted; GPT-5 Nano is proprietary.

GPT-5 Nano is the newest, released Aug 7, 2025. Qwen3 235B-A22B Thinking 2507 came out Jul 25, 2025. Knowledge cutoff: GPT-5 Nano May 30, 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 Nov 2, 2026.