Comprehensive side-by-side LLM comparison
DeepSeek-V3.1 leads with 2.1% higher average benchmark score. GPT-4.1 nano offers 752.7K more tokens in context window than DeepSeek-V3.1. GPT-4.1 nano is $0.77 cheaper per million tokens. GPT-4.1 nano supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
DeepSeek
DeepSeek-V3.1 is a language model developed by DeepSeek. The model shows competitive results across 16 benchmarks. It excels particularly in SimpleQA (93.4%), MMLU-Redux (91.8%), MMLU-Pro (83.7%). It supports a 328K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.
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.
3 months newer
DeepSeek-V3.1
DeepSeek
2025-01-10
GPT-4.1 nano
OpenAI
2025-04-14
Cost per million tokens (USD)
DeepSeek-V3.1
GPT-4.1 nano
Context window and performance specifications
Average performance across 38 common benchmarks
DeepSeek-V3.1
GPT-4.1 nano
GPT-4.1 nano
2024-05-31
Available providers and their performance metrics
DeepSeek-V3.1
DeepInfra
Novita
GPT-4.1 nano
DeepSeek-V3.1
GPT-4.1 nano
DeepSeek-V3.1
GPT-4.1 nano
OpenAI