Comprehensive side-by-side LLM comparison
Gemini 2.5 Pro leads with 30.5% higher average benchmark score. Gemini 2.5 Pro offers 589.8K more tokens in context window than Kimi K2 0905. Kimi K2 0905 is $8.15 cheaper per million tokens. Gemini 2.5 Pro supports multimodal inputs. Overall, Gemini 2.5 Pro 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 0905 is a language model developed by Moonshot AI. This model demonstrates exceptional performance with an average score of 84.0% across 6 benchmarks. It excels particularly in HumanEval (94.5%), MMLU (90.2%), MATH (89.1%). It supports a 524K token context window for handling large documents. The model is available through 2 API providers. Released in 2025, it represents Moonshot AI's latest advancement in AI technology.
3 months newer
Gemini 2.5 Pro
2025-05-20
Kimi K2 0905
Moonshot AI
2025-09-05
Cost per million tokens (USD)
Gemini 2.5 Pro
Kimi K2 0905
Context window and performance specifications
Average performance across 20 common benchmarks
Gemini 2.5 Pro
Kimi K2 0905
Gemini 2.5 Pro
2025-01-31
Available providers and their performance metrics
Gemini 2.5 Pro
ZeroEval
Gemini 2.5 Pro
Kimi K2 0905
Gemini 2.5 Pro
Kimi K2 0905
Kimi K2 0905
Novita
ZeroEval