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Phi-3.5-mini-instruct vs Qwen2.5-Omni-7B
Comprehensive side-by-side LLM comparison
Qwen2.5-Omni-7B leads with 7.5% higher average benchmark score. Qwen2.5-Omni-7B supports multimodal inputs. Overall, Qwen2.5-Omni-7B is the stronger choice for coding tasks.
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Microsoft
Phi-3.5 Mini was developed by Microsoft as a small language model designed to deliver impressive performance despite its compact size. Built with efficiency in mind, it demonstrates that capable language understanding and generation can be achieved with fewer parameters, making AI more accessible for edge and resource-constrained deployments.
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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-mini-instruct
Microsoft
2024-08-23
Qwen2.5-Omni-7B
Alibaba Cloud / Qwen Team
2025-03-27
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Performance Metrics
Context window and performance specifications
Average performance across 6 common benchmarks
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Phi-3.5-mini-instruct
Average Score:57.5%
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Qwen2.5-Omni-7B
Average Score:65.0%(+7.5%)
Provider Availability & Performance
Available providers and their performance metrics
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Phi-3.5-mini-instruct
1 providers
Azure
Throughput: 23 tok/s
Latency: 0.52ms
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Qwen2.5-Omni-7B
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Phi-3.5-mini-instruct
Avg Score:57.5%
Providers:1
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Qwen2.5-Omni-7B
Avg Score:65.0%(+7.5%)
Providers:0