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DeepSeek VL2 Small vs Qwen2.5-Omni-7B
Comprehensive side-by-side LLM comparison
Qwen2.5-Omni-7B leads with 4.5% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-VL2-Small was created as a compact vision-language variant, designed to bring multimodal capabilities to applications with limited computational resources. Built to provide visual and textual understanding in a more efficient package, it serves use cases requiring practical deployment of vision-language AI.
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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 VL2 Small
DeepSeek
2024-12-13
Qwen2.5-Omni-7B
Alibaba Cloud / Qwen Team
2025-03-27
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Average performance across 9 common benchmarks
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DeepSeek VL2 Small
Average Score:72.3%
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Qwen2.5-Omni-7B
Average Score:76.8%(+4.5%)
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek VL2 Small
0 providers
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Qwen2.5-Omni-7B
0 providers
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DeepSeek VL2 Small
Avg Score:72.3%
Providers:0
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Qwen2.5-Omni-7B
Avg Score:76.8%(+4.5%)
Providers:0