Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 9.7% higher average benchmark score. GPT-4.1 nano offers 824.3K more tokens in context window than Pixtral Large. GPT-4.1 nano is $7.50 cheaper per million tokens. Overall, GPT-4.1 nano is the stronger choice for coding tasks.
OpenAI
GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. 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.
Mistral AI
Pixtral Large is a multimodal language model developed by Mistral AI. This model demonstrates exceptional performance with an average score of 80.5% across 7 benchmarks. It excels particularly in AI2D (93.8%), DocVQA (93.3%), ChartQA (88.1%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Mistral AI's latest advancement in AI technology.
4 months newer
Pixtral Large
Mistral AI
2024-11-18
GPT-4.1 nano
OpenAI
2025-04-14
Cost per million tokens (USD)
GPT-4.1 nano
Pixtral Large
Context window and performance specifications
Average performance across 30 common benchmarks
GPT-4.1 nano
Pixtral Large
GPT-4.1 nano
2024-05-31
Available providers and their performance metrics
GPT-4.1 nano
OpenAI
Pixtral Large
GPT-4.1 nano
Pixtral Large
GPT-4.1 nano
Pixtral Large
Mistral AI