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DeepSeek-V3 vs Phi-3.5-vision-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-vision-instruct supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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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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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.
4 months newer
Phi-3.5-vision-instruct
Microsoft
2024-08-23
DeepSeek-V3
DeepSeek
2024-12-25
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Performance Metrics
Context window and performance specifications
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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Phi-3.5-vision-instruct
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DeepSeek-V3
Avg Score:0.0%
Providers:1
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Phi-3.5-vision-instruct
Avg Score:0.0%
Providers:0