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DeepSeek-V2.5 vs Qwen2.5 72B Instruct
Comprehensive side-by-side LLM comparison
Qwen2.5 72B Instruct leads with 2.7% higher average benchmark score. Qwen2.5 72B Instruct offers 122.9K more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. Both models have their strengths depending on your specific coding needs.
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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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Alibaba Cloud / Qwen Team
Qwen 2.5 72B was developed as the flagship text model in the Qwen 2.5 series, designed to provide advanced language capabilities with 72 billion parameters. Built to compete with frontier models in reasoning, coding, and general language tasks, it represents Qwen's most capable instruction-following model in this generation.
4 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Qwen2.5 72B Instruct
Alibaba Cloud / Qwen Team
2024-09-19
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V2.5
Input:$0.14
Output:$0.28($0.33 cheaper)
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Qwen2.5 72B Instruct
Input:$0.35
Output:$0.40
Performance Metrics
Context window and performance specifications
Average performance across 6 common benchmarks
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DeepSeek-V2.5
Average Score:84.3%
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Qwen2.5 72B Instruct
Average Score:87.0%(+2.7%)
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:84.3%
Providers:3
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Qwen2.5 72B Instruct
Avg Score:87.0%(+2.7%)
Providers:4