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DeepSeek-V2.5 vs Qwen2.5 14B Instruct
Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 1.5% higher average benchmark score. DeepSeek-V2.5 is available on 3 providers. 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 14B was developed as a mid-sized instruction-tuned model, designed to balance capability and efficiency for diverse language tasks. Built with 14 billion parameters, it provides strong performance for applications requiring reliable instruction-following without the resource demands of larger models.
4 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Qwen2.5 14B Instruct
Alibaba Cloud / Qwen Team
2024-09-19
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Performance Metrics
Context window and performance specifications
Average performance across 5 common benchmarks
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DeepSeek-V2.5
Average Score:84.7%(+1.5%)
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Qwen2.5 14B Instruct
Average Score:83.2%
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:84.7%(+1.5%)
Providers:3
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Qwen2.5 14B Instruct
Avg Score:83.2%
Providers:0