Comprehensive side-by-side LLM comparison
Kimi K2 Instruct leads with 28.5% higher average benchmark score. Gemini 2.5 Pro offers 852.0K more tokens in context window than Kimi K2 Instruct. Kimi K2 Instruct is $8.38 cheaper per million tokens. Gemini 2.5 Pro supports multimodal inputs. Overall, Kimi K2 Instruct is the stronger choice for coding tasks.
Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 69.6% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. 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 Google'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.
1 month newer
Gemini 2.5 Pro
2025-05-20
Kimi K2 Instruct
Moonshot AI
2025-07-11
Cost per million tokens (USD)
Gemini 2.5 Pro
Kimi K2 Instruct
Context window and performance specifications
Average performance across 44 common benchmarks
Gemini 2.5 Pro
Kimi K2 Instruct
Gemini 2.5 Pro
2025-01-31
Available providers and their performance metrics
Gemini 2.5 Pro
ZeroEval
Gemini 2.5 Pro
Kimi K2 Instruct
Gemini 2.5 Pro
Kimi K2 Instruct
Kimi K2 Instruct
Novita