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DeepSeek-R1 vs Gemini 2.0 Flash Thinking
Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash Thinking supports multimodal inputs. DeepSeek-R1 is available on 5 providers. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-R1 was developed as a reasoning-focused language model, designed to combine chain-of-thought reasoning with reinforcement learning techniques. Built to excel at complex problem-solving through trial-and-error learning and deliberate analytical processes, it demonstrates the power of efficient training methods in open-source model development.
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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.
1 days newer
DeepSeek-R1
DeepSeek
2025-01-20
Gemini 2.0 Flash Thinking
2025-01-21
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Performance Metrics
Context window and performance specifications
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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
5 providers
DeepInfra
Throughput: 0.9 tok/s
Latency: 0.3ms
DeepSeek
Throughput: 9 tok/s
Latency: 0.3ms
Fireworks
Throughput: 2.1 tok/s
Latency: 0.3ms
Together
Throughput: 4 tok/s
Latency: 0.6ms
ZeroEval
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DeepSeek-R1
Avg Score:0.0%
Providers:5
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Gemini 2.0 Flash Thinking
Avg Score:0.0%
Providers:0