Comprehensive side-by-side LLM comparison
Kimi K2 Instruct leads with 35.6% higher average benchmark score. Gemini 2.5 Flash offers 852.0K more tokens in context window than Kimi K2 Instruct. Both models have similar pricing. Gemini 2.5 Flash supports multimodal inputs. Overall, Kimi K2 Instruct is the stronger choice for coding tasks.
Gemini 2.5 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 62.5% across 14 benchmarks. It excels particularly in Global-MMLU-Lite (88.4%), AIME 2024 (88.0%), FACTS Grounding (85.3%). 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 Flash
2025-05-20
Kimi K2 Instruct
Moonshot AI
2025-07-11
Cost per million tokens (USD)
Gemini 2.5 Flash
Kimi K2 Instruct
Context window and performance specifications
Average performance across 42 common benchmarks
Gemini 2.5 Flash
Kimi K2 Instruct
Gemini 2.5 Flash
2025-01-31
Available providers and their performance metrics
Gemini 2.5 Flash
ZeroEval
Gemini 2.5 Flash
Kimi K2 Instruct
Gemini 2.5 Flash
Kimi K2 Instruct
Kimi K2 Instruct
Novita