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DeepSeek VL2 vs Qwen2.5-Omni-7B
Comprehensive side-by-side LLM comparison
Qwen2.5-Omni-7B leads with 33.5% higher average benchmark score. Overall, Qwen2.5-Omni-7B is the stronger choice for coding tasks.
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DeepSeek
DeepSeek VL2 is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 70.9% across 14 benchmarks. It excels particularly in DocVQA (93.3%), ChartQA (86.0%), TextVQA (84.2%). It supports a 259K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents DeepSeek's latest advancement in AI technology.
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Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B is a multimodal language model developed by Alibaba Cloud / Qwen Team. The model shows competitive results across 45 benchmarks. It excels particularly in DocVQA (95.2%), VocalSound (93.9%), GSM8k (88.7%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
3 months newer
DeepSeek VL2
DeepSeek
2024-12-13
Qwen2.5-Omni-7B
Alibaba Cloud / Qwen Team
2025-03-27
Performance Metrics
Context window and performance specifications
Average performance across 50 common benchmarks
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DeepSeek VL2
Average Score:19.9%
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Qwen2.5-Omni-7B
Average Score:53.3%(+33.5%)
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek VL2
1 providers
Replicate
Throughput: 22 tok/s
Latency: 0.5ms
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Qwen2.5-Omni-7B
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DeepSeek VL2
Avg Score:19.9%
Providers:1
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Qwen2.5-Omni-7B
Avg Score:53.3%(+33.5%)
Providers:0