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Phi-3.5-mini-instruct vs Qwen3-235B-A22B-Thinking-2507
Comprehensive side-by-side LLM comparison
Qwen3-235B-A22B-Thinking-2507 leads with 43.9% higher average benchmark score. Qwen3-235B-A22B-Thinking-2507 offers 131.1K more tokens in context window than Phi-3.5-mini-instruct. Phi-3.5-mini-instruct is $3.10 cheaper per million tokens. Overall, Qwen3-235B-A22B-Thinking-2507 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
Qwen3 235B Thinking was developed as a reasoning-enhanced variant, designed to incorporate extended thinking capabilities into the large-scale Qwen3 architecture. Built to combine deliberate analytical processing with mixture-of-experts efficiency, it serves tasks requiring both deep reasoning and computational practicality.
11 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
Qwen3-235B-A22B-Thinking-2507
Alibaba Cloud / Qwen Team
2025-07-25
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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($3.10 cheaper)
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Qwen3-235B-A22B-Thinking-2507
Input:$0.30
Output:
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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Phi-3.5-mini-instruct
Average Score:38.9%
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Qwen3-235B-A22B-Thinking-2507
Average Score:82.8%(+43.9%)
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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Qwen3-235B-A22B-Thinking-2507
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Phi-3.5-mini-instruct
Avg Score:38.9%
Providers:1
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Qwen3-235B-A22B-Thinking-2507
Avg Score:82.8%(+43.9%)
Providers:1