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DeepSeek VL2 vs Phi-3.5-vision-instruct
Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 7.4% higher average benchmark score. Overall, DeepSeek VL2 is the stronger choice for coding tasks.
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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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Microsoft
Phi-3.5 Vision was developed as a multimodal variant of Phi-3.5, designed to understand and reason about both images and text. Built to extend the Phi family's efficiency into vision-language tasks, it enables compact multimodal AI for practical applications.
3 months newer
Phi-3.5-vision-instruct
Microsoft
2024-08-23
DeepSeek VL2
DeepSeek
2024-12-13
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Performance Metrics
Context window and performance specifications
Average performance across 6 common benchmarks
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DeepSeek VL2
Average Score:74.2%(+7.4%)
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Phi-3.5-vision-instruct
Average Score:66.8%
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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Phi-3.5-vision-instruct
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DeepSeek VL2
Avg Score:74.2%(+7.4%)
Providers:1
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Phi-3.5-vision-instruct
Avg Score:66.8%
Providers:0