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DeepSeek R1 Zero vs Gemini 2.5 Pro
Comprehensive side-by-side LLM comparison
Gemini 2.5 Pro leads with 44.9% higher average benchmark score. Gemini 2.5 Pro supports multimodal inputs. Gemini 2.5 Pro is available on 2 providers. Overall, Gemini 2.5 Pro 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 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 69.6% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 2 API providers. 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.
4 months newer
DeepSeek R1 Zero
DeepSeek
2025-01-20
Gemini 2.5 Pro
2025-05-20
Performance Metrics
Context window and performance specifications
Average performance across 18 common benchmarks
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DeepSeek R1 Zero
Average Score:17.0%
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Gemini 2.5 Pro
Average Score:61.9%(+44.9%)
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Knowledge Cutoff
Training data recency comparison
Gemini 2.5 Pro
2025-01-31
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 2.5 Pro
2 providers
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DeepSeek R1 Zero
Avg Score:17.0%
Providers:0
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Gemini 2.5 Pro
Avg Score:61.9%(+44.9%)
Providers:2