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Gemini 2.0 Flash-Lite vs Kimi-k1.5
Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash-Lite leads with 1.5% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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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.
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Moonshot AI
Kimi-k1.5 is a multimodal language model developed by Moonshot AI. This model demonstrates exceptional performance with an average score of 81.7% across 9 benchmarks. It excels particularly in MATH-500 (96.2%), CLUEWSC (91.4%), C-Eval (88.3%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Moonshot AI's latest advancement in AI technology.
16 days newer
Kimi-k1.5
Moonshot AI
2025-01-20
Gemini 2.0 Flash-Lite
2025-02-05
Performance Metrics
Context window and performance specifications
Average performance across 21 common benchmarks
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Gemini 2.0 Flash-Lite
Average Score:36.5%(+1.5%)
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Kimi-k1.5
Average Score:35.0%
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash-Lite
2024-06-01
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-Lite
1 providers
Throughput: 85 tok/s
Latency: 0.7ms
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Kimi-k1.5
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Gemini 2.0 Flash-Lite
Avg Score:36.5%(+1.5%)
Providers:1
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Kimi-k1.5
Avg Score:35.0%
Providers:0