Model Comparison
o1 vs Qwen3-235B-A22B-Instruct-2507Which is better in 2026?
Both models are evenly matched across the benchmarks. Qwen3-235B-A22B-Instruct-2507 is 84.0x cheaper per token.
Verdict: o1 vs Qwen3-235B-A22B-Instruct-2507 — which is better?
o1 (by OpenAI) and Qwen3-235B-A22B-Instruct-2507 (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 outperforms in 1 benchmarks (GPQA), while Qwen3-235B-A22B-Instruct-2507 is better at 1 benchmark (SimpleQA). Both models are evenly matched across the benchmarks.
On price, Qwen3-235B-A22B-Instruct-2507 is roughly 84.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3-235B-A22B-Instruct-2507 also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Choose o1 if…
- you want predictable pricing at $15.00/M input and $60.00/M output
Choose Qwen3-235B-A22B-Instruct-2507 if…
- cost matters — it's about 84.0x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Jul 2025
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
o1 outperforms in 1 benchmarks (GPQA), while Qwen3-235B-A22B-Instruct-2507 is better at 1 benchmark (SimpleQA).
Both models are evenly matched across the benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, o1 ($15.00/1M tokens) is 100.0x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.15/1M tokens).
For output processing, o1 ($60.00/1M tokens) is 75.0x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.80/1M tokens).
In conclusion, o1 is more expensive than Qwen3-235B-A22B-Instruct-2507.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3-235B-A22B-Instruct-2507 accepts 262,144 input tokens compared to o1's 200,000 tokens. Qwen3-235B-A22B-Instruct-2507 can generate longer responses up to 131,072 tokens, while o1 is limited to 100,000 tokens.
License
Usage and distribution terms
o1 is licensed under a proprietary license, while Qwen3-235B-A22B-Instruct-2507 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 was released on 2024-12-17, while Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.
Qwen3-235B-A22B-Instruct-2507 is 7 months newer than o1.
Dec 17, 2024
1.6 years ago
Jul 22, 2025
1.0 years ago
7mo 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 is available from Azure, OpenAI. Qwen3-235B-A22B-Instruct-2507 is available from Fireworks, Novita.
o1
Qwen3-235B-A22B-Instruct-2507
Outputs Comparison
Key Takeaways
o1
View detailsOpenAI
Qwen3-235B-A22B-Instruct-2507
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against o1 and Qwen3-235B-A22B-Instruct-2507 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about o1 vs Qwen3-235B-A22B-Instruct-2507.