Comprehensive side-by-side LLM comparison
GPT-5 nano leads with 32.8% higher average benchmark score. GPT-5 nano offers 272.0K more tokens in context window than Devstral Small 1.1. Both models have similar pricing. GPT-5 nano supports multimodal inputs. Overall, GPT-5 nano is the stronger choice for coding tasks.
Mistral AI
Devstral Small 1.1 is a language model developed by Mistral AI. The model shows competitive results across 1 benchmarks. Notable strengths include SWE-Bench Verified (53.6%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Mistral AI's latest advancement in AI technology.
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.
27 days newer
Devstral Small 1.1
Mistral AI
2025-07-11
GPT-5 nano
OpenAI
2025-08-07
Cost per million tokens (USD)
Devstral Small 1.1
GPT-5 nano
Context window and performance specifications
Average performance across 6 common benchmarks
Devstral Small 1.1
GPT-5 nano
GPT-5 nano
2024-05-30
Available providers and their performance metrics
Devstral Small 1.1
Mistral AI
GPT-5 nano
Devstral Small 1.1
GPT-5 nano
Devstral Small 1.1
GPT-5 nano
OpenAI
ZeroEval