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DeepSeek VL2 vs Qwen2.5 VL 7B Instruct
Comprehensive side-by-side LLM comparison
Qwen2.5 VL 7B Instruct leads with 3.2% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-VL2 was developed as a vision-language model, designed to handle both visual and textual inputs for multimodal understanding tasks. Built to extend DeepSeek's capabilities beyond text-only processing, it enables applications requiring integrated analysis of images and language.
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Alibaba Cloud / Qwen Team
Qwen2.5-VL 7B was developed as an efficient vision-language model, designed to provide multimodal understanding with minimal computational requirements. Built with 7 billion parameters for integrated visual and textual processing, it serves applications requiring practical vision-language capabilities with constrained resources.
1 month newer
DeepSeek VL2
DeepSeek
2024-12-13
Qwen2.5 VL 7B Instruct
Alibaba Cloud / Qwen Team
2025-01-26
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Performance Metrics
Context window and performance specifications
Average performance across 9 common benchmarks
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DeepSeek VL2
Average Score:75.4%
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Qwen2.5 VL 7B Instruct
Average Score:78.6%(+3.2%)
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 VL 7B Instruct
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DeepSeek VL2
Avg Score:75.4%
Providers:1
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Qwen2.5 VL 7B Instruct
Avg Score:78.6%(+3.2%)
Providers:0