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DeepSeek-V2.5 vs Qwen2.5-Omni-7B
Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 6.6% higher average benchmark score. Qwen2.5-Omni-7B 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 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
Qwen2.5-Omni 7B was created as a multimodal model supporting text, audio, and other modalities, designed to provide integrated understanding across diverse input types. Built with 7 billion parameters for efficient omni-modal processing, it extends AI capabilities beyond traditional text-only or vision-language boundaries.
10 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Qwen2.5-Omni-7B
Alibaba Cloud / Qwen Team
2025-03-27
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Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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DeepSeek-V2.5
Average Score:86.3%(+6.6%)
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Qwen2.5-Omni-7B
Average Score:79.6%
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:86.3%(+6.6%)
Providers:3
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Qwen2.5-Omni-7B
Avg Score:79.6%
Providers:0