Model Comparison
o1-mini vs QwQ-32B-PreviewWhich is better in 2026?
QwQ-32B-Preview significantly outperforms across most benchmarks. QwQ-32B-Preview is 32.3x cheaper per token.
Verdict: o1-mini vs QwQ-32B-Preview — which is better?
o1-mini (by OpenAI) and QwQ-32B-Preview (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
o1-mini outperforms in 0 benchmarks, while QwQ-32B-Preview is better at 2 benchmarks (GPQA, MATH-500). QwQ-32B-Preview significantly outperforms across most benchmarks.
On price, QwQ-32B-Preview is roughly 32.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
o1-mini also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose o1-mini if…
- you process long inputs — it offers a 128,000 token context window
Choose QwQ-32B-Preview if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- cost matters — it's about 32.3x cheaper per token
- you want the most recent training data — it shipped Nov 2024
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
o1-mini outperforms in 0 benchmarks, while QwQ-32B-Preview is better at 2 benchmarks (GPQA, MATH-500).
QwQ-32B-Preview significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, o1-mini ($3.00/1M tokens) is 20.0x more expensive than QwQ-32B-Preview ($0.15/1M tokens).
For output processing, o1-mini ($12.00/1M tokens) is 60.0x more expensive than QwQ-32B-Preview ($0.20/1M tokens).
In conclusion, o1-mini is more expensive than QwQ-32B-Preview.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
o1-mini accepts 128,000 input tokens compared to QwQ-32B-Preview's 32,768 tokens. o1-mini can generate longer responses up to 65,536 tokens, while QwQ-32B-Preview is limited to 32,768 tokens.
License
Usage and distribution terms
o1-mini is licensed under a proprietary license, while QwQ-32B-Preview 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 QwQ-32B-Preview was released on 2024-11-28.
QwQ-32B-Preview is 3 months newer than o1-mini.
Sep 12, 2024
1.9 years ago
Nov 28, 2024
1.7 years ago
2mo newerKnowledge Cutoff
When training data ends
QwQ-32B-Preview has a documented knowledge cutoff of 2024-11-28, while o1-mini's cutoff date is not specified.
We can confirm QwQ-32B-Preview's training data extends to 2024-11-28, but cannot make a direct comparison without o1-mini's cutoff date.
—
Nov 2024
Provider Availability
o1-mini is available from OpenAI, Azure. QwQ-32B-Preview is available from DeepInfra, Hyperbolic, Fireworks, Together.
o1-mini
QwQ-32B-Preview
Outputs Comparison
Key Takeaways
o1-mini
View detailsOpenAI
QwQ-32B-Preview
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against o1-mini and QwQ-32B-Preview side-by-side, then vote on the output you prefer.
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FAQ
Common questions about o1-mini vs QwQ-32B-Preview.