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DeepSeek-V3 vs Gemini 2.0 Flash Thinking
Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash Thinking leads with 24.6% higher average benchmark score. Gemini 2.0 Flash Thinking supports multimodal inputs. Overall, Gemini 2.0 Flash Thinking is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3 was introduced as a major architectural advancement, developed with 671B mixture-of-experts parameters and trained on 14.8 trillion tokens. Built to be three times faster than V2 while maintaining open-source availability, it demonstrates competitive performance against frontier closed-source models and represents a significant leap in efficient large-scale model design.
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Gemini 2.0 Flash Thinking was developed to incorporate extended reasoning capabilities into the Flash family, designed to combine quick response times with deeper analytical processing. Built to handle tasks requiring both speed and thoughtful problem-solving, it bridges the gap between fast inference and reasoning-enhanced models.
27 days newer
DeepSeek-V3
DeepSeek
2024-12-25
Gemini 2.0 Flash Thinking
2025-01-21
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Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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DeepSeek-V3
Average Score:49.1%
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Gemini 2.0 Flash Thinking
Average Score:73.8%(+24.6%)
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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-V3
1 providers
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
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Gemini 2.0 Flash Thinking
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DeepSeek-V3
Avg Score:49.1%
Providers:1
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Gemini 2.0 Flash Thinking
Avg Score:73.8%(+24.6%)
Providers:0