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Phi-4-multimodal-instruct vs Qwen2.5 VL 32B Instruct
Comprehensive side-by-side LLM comparison
Qwen2.5 VL 32B Instruct leads with 9.6% higher average benchmark score. Overall, Qwen2.5 VL 32B Instruct is the stronger choice for coding tasks.
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Microsoft
Phi-4 Multimodal was created to handle multiple input modalities including text, images, and potentially other formats. Built to extend Phi-4's efficiency into multimodal applications, it demonstrates that compact models can successfully integrate diverse information types.
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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.
27 days newer
Phi-4-multimodal-instruct
Microsoft
2025-02-01
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 4 common benchmarks
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Phi-4-multimodal-instruct
Average Score:64.9%
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Qwen2.5 VL 32B Instruct
Average Score:74.4%(+9.6%)
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Knowledge Cutoff
Training data recency comparison
Phi-4-multimodal-instruct
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-multimodal-instruct
1 providers
DeepInfra
Throughput: 25 tok/s
Latency: 0.5ms
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Qwen2.5 VL 32B Instruct
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Phi-4-multimodal-instruct
Avg Score:64.9%
Providers:1
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Qwen2.5 VL 32B Instruct
Avg Score:74.4%(+9.6%)
Providers:0