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DeepSeek VL2 vs Phi 4 Mini
Comprehensive side-by-side LLM comparison
Phi 4 Mini leads with 3.8% higher average benchmark score. DeepSeek VL2 supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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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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Microsoft
Phi 4 Mini is a language model developed by Microsoft. It achieves strong performance with an average score of 65.4% across 17 benchmarks. It excels particularly in GSM8k (88.6%), ARC-C (83.7%), BoolQ (81.2%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.
1 month newer
DeepSeek VL2
DeepSeek
2024-12-13
Phi 4 Mini
Microsoft
2025-02-01
Performance Metrics
Context window and performance specifications
Average performance across 31 common benchmarks
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DeepSeek VL2
Average Score:32.0%
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Phi 4 Mini
Average Score:35.8%(+3.8%)
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Knowledge Cutoff
Training data recency comparison
Phi 4 Mini
2024-06-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
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 4 Mini
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DeepSeek VL2
Avg Score:32.0%
Providers:1
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Phi 4 Mini
Avg Score:35.8%(+3.8%)
Providers:0