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o4-mini vs Qwen3-235B-A22B-Thinking-2507
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Qwen3-235B-A22B-Thinking-2507 offers 87.1K more tokens in context window than o4-mini. Qwen3-235B-A22B-Thinking-2507 is $2.20 cheaper per million tokens. o4-mini supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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OpenAI
o4-mini was created as part of the next generation of OpenAI's reasoning models, designed to continue advancing the balance between analytical capability and operational efficiency. Built to bring cutting-edge reasoning techniques to applications requiring quick turnaround, it represents the evolution of compact reasoning-focused models.
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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.
3 months newer
o4-mini
OpenAI
2025-04-16
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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o4-mini
Input:$1.10
Output:$4.40
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Qwen3-235B-A22B-Thinking-2507
Input:$0.30
Output:$3.00($2.20 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 5 common benchmarks
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o4-mini
Average Score:62.0%(+0.9%)
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Qwen3-235B-A22B-Thinking-2507
Average Score:61.1%
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Knowledge Cutoff
Training data recency comparison
o4-mini
2024-05-31
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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o4-mini
1 providers
OpenAI
Throughput: 115 tok/s
Latency: 5.2ms
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Qwen3-235B-A22B-Thinking-2507
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o4-mini
Avg Score:62.0%(+0.9%)
Providers:1
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Qwen3-235B-A22B-Thinking-2507
Avg Score:61.1%
Providers:1