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Gemini 2.0 Flash vs Kimi K2 Base
Comprehensive side-by-side LLM comparison
Kimi K2 Base leads with 1.4% higher average benchmark score. Gemini 2.0 Flash supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Gemini 2.0 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 66.7% across 13 benchmarks. It excels particularly in Natural2Code (92.9%), MATH (89.7%), FACTS Grounding (83.6%). 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 2024, it represents Google's latest advancement in AI technology.
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Moonshot AI
Kimi K2 Base is a language model developed by Moonshot AI. It achieves strong performance with an average score of 69.2% across 13 benchmarks. It excels particularly in C-Eval (92.5%), GSM8k (92.1%), MMLU-redux-2.0 (90.2%). 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.
7 months newer
Gemini 2.0 Flash
2024-12-01
Kimi K2 Base
Moonshot AI
2025-07-11
Performance Metrics
Context window and performance specifications
Average performance across 23 common benchmarks
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Gemini 2.0 Flash
Average Score:37.7%
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Kimi K2 Base
Average Score:39.1%(+1.4%)
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash
2024-08-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemini 2.0 Flash
1 providers
Throughput: 183 tok/s
Latency: 0.4ms
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Kimi K2 Base
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Gemini 2.0 Flash
Avg Score:37.7%
Providers:1
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Kimi K2 Base
Avg Score:39.1%(+1.4%)
Providers:0