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Phi-3.5-MoE-instruct vs Qwen2.5-Omni-7B
Comprehensive side-by-side LLM comparison
Qwen2.5-Omni-7B leads with 1.4% higher average benchmark score. Qwen2.5-Omni-7B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Microsoft
Phi-3.5 MoE was created using a mixture-of-experts architecture, designed to provide enhanced capabilities while maintaining efficiency through sparse activation. Built to combine the benefits of larger models with practical computational requirements, it represents Microsoft's exploration of efficient scaling techniques.
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Alibaba Cloud / Qwen Team
Qwen2.5-Omni 7B was created as a multimodal model supporting text, audio, and other modalities, designed to provide integrated understanding across diverse input types. Built with 7 billion parameters for efficient omni-modal processing, it extends AI capabilities beyond traditional text-only or vision-language boundaries.
7 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
Qwen2.5-Omni-7B
Alibaba Cloud / Qwen Team
2025-03-27
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Average performance across 6 common benchmarks
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Phi-3.5-MoE-instruct
Average Score:63.6%
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Qwen2.5-Omni-7B
Average Score:65.0%(+1.4%)
Provider Availability & Performance
Available providers and their performance metrics
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Phi-3.5-MoE-instruct
0 providers
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Qwen2.5-Omni-7B
0 providers
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Phi-3.5-MoE-instruct
Avg Score:63.6%
Providers:0
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Qwen2.5-Omni-7B
Avg Score:65.0%(+1.4%)
Providers:0