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Gemini 2.5 Flash-Lite vs Kimi K2-Instruct-0905
Comprehensive side-by-side LLM comparison
Kimi K2-Instruct-0905 leads with 36.6% higher average benchmark score. Gemini 2.5 Flash-Lite supports multimodal inputs. Overall, Kimi K2-Instruct-0905 is the stronger choice for coding tasks.
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Gemini 2.5 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in FACTS Grounding (84.1%), Global-MMLU-Lite (81.1%), MMMU (72.9%). 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.
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Moonshot AI
Kimi K2-Instruct-0905 is a language model developed by Moonshot AI. It achieves strong performance with an average score of 64.1% across 29 benchmarks. It excels particularly in MATH-500 (97.4%), MMLU-Redux (92.7%), IFEval (89.8%). 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.
2 months newer
Gemini 2.5 Flash-Lite
2025-06-17
Kimi K2-Instruct-0905
Moonshot AI
2025-09-05
Performance Metrics
Context window and performance specifications
Average performance across 35 common benchmarks
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Gemini 2.5 Flash-Lite
Average Score:15.2%
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Kimi K2-Instruct-0905
Average Score:51.8%(+36.6%)
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Knowledge Cutoff
Training data recency comparison
Gemini 2.5 Flash-Lite
2025-01-01
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 2.5 Flash-Lite
1 providers
Throughput: 5.69 tok/s
Latency: 0.44ms
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Kimi K2-Instruct-0905
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Gemini 2.5 Flash-Lite
Avg Score:15.2%
Providers:1
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Kimi K2-Instruct-0905
Avg Score:51.8%(+36.6%)
Providers:0