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DeepSeek-V3 vs Qwen2.5-Omni-7B
Comprehensive side-by-side LLM comparison
DeepSeek-V3 leads with 25.1% higher average benchmark score. Qwen2.5-Omni-7B supports multimodal inputs. Overall, DeepSeek-V3 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3 was introduced as a major architectural advancement, developed with 671B mixture-of-experts parameters and trained on 14.8 trillion tokens. Built to be three times faster than V2 while maintaining open-source availability, it demonstrates competitive performance against frontier closed-source models and represents a significant leap in efficient large-scale model design.
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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.
3 months newer
DeepSeek-V3
DeepSeek
2024-12-25
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-V3
Average Score:74.7%(+25.1%)
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Qwen2.5-Omni-7B
Average Score:49.6%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3
1 providers
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
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Qwen2.5-Omni-7B
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DeepSeek-V3
Avg Score:74.7%(+25.1%)
Providers:1
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Qwen2.5-Omni-7B
Avg Score:49.6%
Providers:0