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Gemini 2.0 Flash Thinking vs Gemini 2.0 Flash-Lite
Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash-Lite leads with 38.8% higher average benchmark score. Overall, Gemini 2.0 Flash-Lite is the stronger choice for coding tasks.
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Gemini 2.0 Flash Thinking is a multimodal language model developed by Google. It achieves strong performance with an average score of 74.3% across 3 benchmarks. Notable strengths include MMMU (75.4%), GPQA (74.2%), AIME 2024 (73.3%). 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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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.
15 days newer
Gemini 2.0 Flash Thinking
2025-01-21
Gemini 2.0 Flash-Lite
2025-02-05
Performance Metrics
Context window and performance specifications
Average performance across 14 common benchmarks
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Gemini 2.0 Flash Thinking
Average Score:15.9%
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Gemini 2.0 Flash-Lite
Average Score:54.8%(+38.8%)
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash-Lite
2024-06-01
Gemini 2.0 Flash Thinking
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 Thinking
0 providers
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Gemini 2.0 Flash-Lite
1 providers
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Gemini 2.0 Flash Thinking
Avg Score:15.9%
Providers:0
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Gemini 2.0 Flash-Lite
Avg Score:54.8%(+38.8%)
Providers:1