Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash-Lite leads with 16.4% higher average benchmark score. Gemini 2.0 Flash-Lite offers 532.5K more tokens in context window than Kimi K2 0905. Gemini 2.0 Flash-Lite is $2.73 cheaper per million tokens. Gemini 2.0 Flash-Lite supports multimodal inputs. Overall, Gemini 2.0 Flash-Lite is the stronger choice for coding tasks.
Gemini 2.0 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in MATH (86.8%), FACTS Grounding (83.6%), Global-MMLU-Lite (78.2%). 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 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.
7 months newer
Gemini 2.0 Flash-Lite
2025-02-05
Kimi K2 0905
Moonshot AI
2025-09-05
Cost per million tokens (USD)
Gemini 2.0 Flash-Lite
Kimi K2 0905
Context window and performance specifications
Average performance across 16 common benchmarks
Gemini 2.0 Flash-Lite
Kimi K2 0905
Gemini 2.0 Flash-Lite
2024-06-01
Available providers and their performance metrics
Gemini 2.0 Flash-Lite
Kimi K2 0905
Gemini 2.0 Flash-Lite
Kimi K2 0905
Gemini 2.0 Flash-Lite
Kimi K2 0905
Novita
ZeroEval