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DeepSeek R1 Zero vs Gemini 2.0 Flash Thinking
Comprehensive side-by-side LLM comparison
DeepSeek R1 Zero leads with 16.6% higher average benchmark score. Gemini 2.0 Flash Thinking supports multimodal inputs. Overall, DeepSeek R1 Zero is the stronger choice for coding tasks.
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DeepSeek
DeepSeek R1 Zero is a language model developed by DeepSeek. It achieves strong performance with an average score of 76.5% across 4 benchmarks. It excels particularly in MATH-500 (95.9%), AIME 2024 (86.7%), GPQA (73.3%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.
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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.
1 days newer
DeepSeek R1 Zero
DeepSeek
2025-01-20
Gemini 2.0 Flash Thinking
2025-01-21
Average performance across 5 common benchmarks
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DeepSeek R1 Zero
Average Score:61.2%(+16.6%)
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Gemini 2.0 Flash Thinking
Average Score:44.6%
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Knowledge Cutoff
Training data recency comparison
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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DeepSeek R1 Zero
0 providers
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Gemini 2.0 Flash Thinking
0 providers
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DeepSeek R1 Zero
Avg Score:61.2%(+16.6%)
Providers:0
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Gemini 2.0 Flash Thinking
Avg Score:44.6%
Providers:0