Comprehensive side-by-side LLM comparison
Kimi K2 Instruct leads with 29.5% higher average benchmark score. GPT-4.1 nano offers 818.2K more tokens in context window than Kimi K2 Instruct. GPT-4.1 nano is $2.37 cheaper per million tokens. GPT-4.1 nano supports multimodal inputs. Overall, Kimi K2 Instruct 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.
Moonshot AI
Kimi K2 Instruct is a language model developed by Moonshot AI. It achieves strong performance with an average score of 66.7% across 38 benchmarks. It excels particularly in MATH-500 (97.4%), GSM8k (97.3%), CBNSL (95.6%). It supports a 262K 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 Moonshot AI's latest advancement in AI technology.
2 months newer
GPT-4.1 nano
OpenAI
2025-04-14
Kimi K2 Instruct
Moonshot AI
2025-07-11
Cost per million tokens (USD)
GPT-4.1 nano
Kimi K2 Instruct
Context window and performance specifications
Average performance across 57 common benchmarks
GPT-4.1 nano
Kimi K2 Instruct
GPT-4.1 nano
2024-05-31
Available providers and their performance metrics
GPT-4.1 nano
OpenAI
Kimi K2 Instruct
GPT-4.1 nano
Kimi K2 Instruct
GPT-4.1 nano
Kimi K2 Instruct
Novita