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DeepSeek-V2.5 vs Gemini 2.0 Flash Thinking
Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 46.9% higher average benchmark score. Gemini 2.0 Flash Thinking supports multimodal inputs. DeepSeek-V2.5 is available on 3 providers. Overall, DeepSeek-V2.5 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V2.5 is a language model developed by DeepSeek. It achieves strong performance with an average score of 71.1% across 15 benchmarks. It excels particularly in GSM8k (95.1%), MT-Bench (90.2%), HumanEval (89.0%). The model is available through 3 API providers. Released in 2024, 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.
8 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Gemini 2.0 Flash Thinking
2025-01-21
Performance Metrics
Context window and performance specifications
Average performance across 18 common benchmarks
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DeepSeek-V2.5
Average Score:59.3%(+46.9%)
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Gemini 2.0 Flash Thinking
Average Score:12.4%
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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-V2.5
3 providers
DeepInfra
Throughput: 63 tok/s
Latency: 0.5ms
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
Hyperbolic
Throughput: 100 tok/s
Latency: 0.5ms
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DeepSeek-V2.5
Avg Score:59.3%(+46.9%)
Providers:3
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Gemini 2.0 Flash Thinking
Avg Score:12.4%
Providers:0