Comprehensive side-by-side LLM comparison
Qwen3 32B leads with 30.6% higher average benchmark score. GPT-5 nano offers 272.0K more tokens in context window than Qwen3 32B. Both models have similar pricing. GPT-5 nano supports multimodal inputs. Overall, Qwen3 32B is the stronger choice for coding tasks.
OpenAI
GPT-5 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 5 benchmarks. It excels particularly in AIME 2025 (85.2%), HMMT 2025 (75.6%), GPQA (71.2%). It supports a 528K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.
Alibaba Cloud / Qwen Team
Qwen3 32B is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 72.0% across 9 benchmarks. It excels particularly in Arena Hard (93.8%), AIME 2024 (81.4%), LiveBench (74.9%). It supports a 256K token context window for handling large documents. The model is available through 3 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
3 months newer
Qwen3 32B
Alibaba Cloud / Qwen Team
2025-04-29
GPT-5 nano
OpenAI
2025-08-07
Cost per million tokens (USD)
GPT-5 nano
Qwen3 32B
Context window and performance specifications
Average performance across 13 common benchmarks
GPT-5 nano
Qwen3 32B
GPT-5 nano
2024-05-30
Available providers and their performance metrics
GPT-5 nano
OpenAI
ZeroEval
GPT-5 nano
Qwen3 32B
GPT-5 nano
Qwen3 32B
Qwen3 32B
DeepInfra
Novita
Sambanova