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Phi-3.5-mini-instruct vs QwQ-32B-Preview
Comprehensive side-by-side LLM comparison
QwQ-32B-Preview leads with 34.8% higher average benchmark score. Phi-3.5-mini-instruct offers 190.5K more tokens in context window than QwQ-32B-Preview. Both models have similar pricing. QwQ-32B-Preview is available on 4 providers. Overall, QwQ-32B-Preview 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
QwQ 32B Preview was introduced as an early access version of the QwQ reasoning model, designed to allow researchers and developers to experiment with advanced analytical capabilities. Built to gather feedback on reasoning-enhanced architecture, it represents an experimental step toward more thoughtful language models.
3 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
QwQ-32B-Preview
Alibaba Cloud / Qwen Team
2024-11-28
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Pricing Comparison
Cost per million tokens (USD)
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10($0.15 cheaper)
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QwQ-32B-Preview
Input:$0.15
Output:$0.20
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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Phi-3.5-mini-instruct
Average Score:30.4%
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QwQ-32B-Preview
Average Score:65.2%(+34.8%)
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Knowledge Cutoff
Training data recency comparison
QwQ-32B-Preview
2024-11-28
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-3.5-mini-instruct
1 providers
Azure
Throughput: 23 tok/s
Latency: 0.52ms
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QwQ-32B-Preview
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Phi-3.5-mini-instruct
Avg Score:30.4%
Providers:1
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QwQ-32B-Preview
Avg Score:65.2%(+34.8%)
Providers:4