Comprehensive side-by-side LLM comparison
Qwen3-235B-A22B-Thinking-2507 leads with 8.8% higher average benchmark score. GPT-5 nano offers 140.9K more tokens in context window than Qwen3-235B-A22B-Thinking-2507. GPT-5 nano is $2.85 cheaper per million tokens. GPT-5 nano supports multimodal inputs. Overall, Qwen3-235B-A22B-Thinking-2507 is the stronger choice for coding tasks.
OpenAI
GPT-5 Nano was developed as the most compact variant in the GPT-5 family, designed for deployment in resource-constrained environments and edge computing scenarios. Built to bring next-generation AI capabilities to devices and applications where latency and efficiency are paramount, it distills GPT-5 innovations into a minimal footprint.
Alibaba Cloud / Qwen Team
Qwen3 235B Thinking was developed as a reasoning-enhanced variant, designed to incorporate extended thinking capabilities into the large-scale Qwen3 architecture. Built to combine deliberate analytical processing with mixture-of-experts efficiency, it serves tasks requiring both deep reasoning and computational practicality.
13 days newer

Qwen3-235B-A22B-Thinking-2507
Alibaba Cloud / Qwen Team
2025-07-25

GPT-5 nano
OpenAI
2025-08-07
Cost per million tokens (USD)

GPT-5 nano

Qwen3-235B-A22B-Thinking-2507
Context window and performance specifications
Average performance across 3 common benchmarks

GPT-5 nano

Qwen3-235B-A22B-Thinking-2507
GPT-5 nano
2024-05-30
Available providers and their performance metrics

GPT-5 nano
OpenAI
ZeroEval


GPT-5 nano

Qwen3-235B-A22B-Thinking-2507

GPT-5 nano

Qwen3-235B-A22B-Thinking-2507
Qwen3-235B-A22B-Thinking-2507
Novita