Model Comparison
o1 vs Qwen3 VL 235B A22B InstructWhich is better in 2026?
Both models are evenly matched across the benchmarks. Qwen3 VL 235B A22B Instruct is 43.9x cheaper per token.
Verdict: o1 vs Qwen3 VL 235B A22B Instruct — which is better?
o1 (by OpenAI) and Qwen3 VL 235B A22B Instruct (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 (MMLU), while Qwen3 VL 235B A22B Instruct is better at 1 benchmark (SimpleQA). Both models are evenly matched across the benchmarks.
On price, Qwen3 VL 235B A22B Instruct is roughly 43.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 235B A22B Instruct 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 VL 235B A22B Instruct if…
- cost matters — it's about 43.9x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
o1 outperforms in 1 benchmarks (MMLU), while Qwen3 VL 235B A22B Instruct 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 50.0x more expensive than Qwen3 VL 235B A22B Instruct ($0.30/1M tokens).
For output processing, o1 ($60.00/1M tokens) is 40.3x more expensive than Qwen3 VL 235B A22B Instruct ($1.49/1M tokens).
In conclusion, o1 is more expensive than Qwen3 VL 235B A22B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3 VL 235B A22B Instruct accepts 262,144 input tokens compared to o1's 200,000 tokens. Qwen3 VL 235B A22B Instruct can generate longer responses up to 262,144 tokens, while o1 is limited to 100,000 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 235B A22B Instruct supports multimodal inputs, whereas o1 does not.
Qwen3 VL 235B A22B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
o1
Qwen3 VL 235B A22B Instruct
License
Usage and distribution terms
o1 is licensed under a proprietary license, while Qwen3 VL 235B A22B Instruct 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 VL 235B A22B Instruct was released on 2025-09-22.
Qwen3 VL 235B A22B Instruct is 9 months newer than o1.
Dec 17, 2024
1.5 years ago
Sep 22, 2025
9 months ago
9mo 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 VL 235B A22B Instruct is available from DeepInfra, Novita.
o1
Qwen3 VL 235B A22B Instruct
Outputs Comparison
Key Takeaways
o1
View detailsOpenAI
Qwen3 VL 235B A22B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against o1 and Qwen3 VL 235B A22B Instruct side-by-side, then vote on the output you prefer.
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FAQ
Common questions about o1 vs Qwen3 VL 235B A22B Instruct.