Model Comparison
o1-mini vs Qwen3-Coder
Comparing o1-mini and Qwen3-Coder across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
o1-mini and Qwen3-Coder don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, o1-mini ($3.00/1M tokens) is 16.7x more expensive than Qwen3-Coder ($0.18/1M tokens).
For output processing, o1-mini ($12.00/1M tokens) is 66.7x more expensive than Qwen3-Coder ($0.18/1M tokens).
In conclusion, o1-mini is more expensive than Qwen3-Coder.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3-Coder accepts 256,000 input tokens compared to o1-mini's 128,000 tokens. Qwen3-Coder can generate longer responses up to 256,000 tokens, while o1-mini is limited to 65,536 tokens.
License
Usage and distribution terms
o1-mini is licensed under a proprietary license, while Qwen3-Coder uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
o1-mini was released on 2024-09-12, while Qwen3-Coder was released on 2025-01-01.
Qwen3-Coder is 4 months newer than o1-mini.
Sep 12, 2024
1.6 years ago
Jan 1, 2025
1.3 years ago
3mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
o1-mini is available from OpenAI, Azure. Qwen3-Coder is available from DeepInfra, Fireworks.
o1-mini
Qwen3-Coder
Outputs Comparison
Key Takeaways
o1-mini
View detailsOpenAI
Qwen3-Coder
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about o1-mini vs Qwen3-Coder