Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 1.6% higher average benchmark score. GPT-4.1 nano offers 944.2K more tokens in context window than Pixtral-12B. Both models have similar pricing. Both models have their strengths depending on your specific coding needs.
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-12B is a multimodal language model developed by Mistral AI. It achieves strong performance with an average score of 66.8% across 12 benchmarks. It excels particularly in DocVQA (90.7%), ChartQA (81.8%), VQAv2 (78.6%). It supports a 136K 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. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Mistral AI's latest advancement in AI technology.
6 months newer
Pixtral-12B
Mistral AI
2024-09-17
GPT-4.1 nano
OpenAI
2025-04-14
Cost per million tokens (USD)
GPT-4.1 nano
Pixtral-12B
Context window and performance specifications
Average performance across 33 common benchmarks
GPT-4.1 nano
Pixtral-12B
GPT-4.1 nano
2024-05-31
Available providers and their performance metrics
GPT-4.1 nano
OpenAI
Pixtral-12B
GPT-4.1 nano
Pixtral-12B
GPT-4.1 nano
Pixtral-12B
Mistral AI