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DeepSeek-V2.5 vs Gemini 2.0 Flash
Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash leads with 15.0% higher average benchmark score. Gemini 2.0 Flash offers 1.0M more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. Gemini 2.0 Flash supports multimodal inputs. DeepSeek-V2.5 is available on 3 providers. Overall, Gemini 2.0 Flash is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V2.5 was developed as an enhanced iteration of the DeepSeek-V2 architecture, designed to incorporate improvements in model quality and efficiency. Built to advance the DeepSeek foundation model series, it provides refined capabilities for general-purpose language understanding and generation tasks.
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Gemini 2.0 Flash was developed as the next generation of Google's fast multimodal model, designed to provide improved performance while maintaining the speed and efficiency that defines the Flash family. Built with enhanced reasoning and generation capabilities, it serves applications requiring both quality and responsiveness.
6 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Gemini 2.0 Flash
2024-12-01
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V2.5
Input:$0.14
Output:$0.28($0.08 cheaper)
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Gemini 2.0 Flash
Input:$0.10
Output:$0.40
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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DeepSeek-V2.5
Average Score:74.7%
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Gemini 2.0 Flash
Average Score:89.7%(+15.0%)
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash
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:74.7%
Providers:3
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Gemini 2.0 Flash
Avg Score:89.7%(+15.0%)
Providers:1