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DeepSeek-V2.5 vs Gemini 1.0 Pro
Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 28.7% higher average benchmark score. Gemini 1.0 Pro offers 24.6K more tokens in context window than DeepSeek-V2.5. DeepSeek-V2.5 is $1.58 cheaper per million tokens. 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 1.0 Pro is a language model developed by Google. The model shows competitive results across 9 benchmarks. Notable strengths include BIG-Bench (75.0%), MMLU (71.8%), WMT23 (71.7%). The model is available through 1 API provider. Released in 2024, it represents Google's latest advancement in AI technology.
2 months newer
Gemini 1.0 Pro
2024-02-15
DeepSeek-V2.5
DeepSeek
2024-05-08
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V2.5
Input:$0.14
Output:$0.28($1.58 cheaper)
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Gemini 1.0 Pro
Input:$0.50
Output:$1.50
Performance Metrics
Context window and performance specifications
Average performance across 22 common benchmarks
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DeepSeek-V2.5
Average Score:48.5%(+28.7%)
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Gemini 1.0 Pro
Average Score:19.8%
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Knowledge Cutoff
Training data recency comparison
Gemini 1.0 Pro
2024-02-01
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:48.5%(+28.7%)
Providers:3
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Gemini 1.0 Pro
Avg Score:19.8%
Providers:1