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Phi 4 vs Qwen2.5 VL 32B Instruct
Comprehensive side-by-side LLM comparison
Phi 4 leads with 1.5% higher average benchmark score. Qwen2.5 VL 32B Instruct supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Microsoft
Phi-4 was introduced as the fourth generation of Microsoft's small language model series, designed to push the boundaries of what compact models can achieve. Built with advanced training techniques and architectural improvements, it demonstrates continued progress in efficient, high-quality language models.
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Alibaba Cloud / Qwen Team
Qwen2.5-VL 32B was developed as a mid-sized vision-language model, designed to balance multimodal capability with practical deployment considerations. Built with 32 billion parameters for vision and language integration, it serves applications requiring strong visual understanding without flagship-scale resources.
2 months newer
Phi 4
Microsoft
2024-12-12
Qwen2.5 VL 32B Instruct
Alibaba Cloud / Qwen Team
2025-02-28
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Performance Metrics
Context window and performance specifications
Average performance across 5 common benchmarks
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Phi 4
Average Score:74.9%(+1.5%)
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Qwen2.5 VL 32B Instruct
Average Score:73.4%
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Knowledge Cutoff
Training data recency comparison
Phi 4
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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Phi 4
1 providers
DeepInfra
Throughput: 33 tok/s
Latency: 0.2ms
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Qwen2.5 VL 32B Instruct
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Phi 4
Avg Score:74.9%(+1.5%)
Providers:1
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Qwen2.5 VL 32B Instruct
Avg Score:73.4%
Providers:0