o3-mini vs Qwen3 VL 235B A22B Thinking
Both models are evenly matched across the benchmarks. Qwen3 VL 235B A22B Thinking is 1.6x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
o3-mini outperforms in 2 benchmarks (IFEval, Multi-IF), while Qwen3 VL 235B A22B Thinking is better at 2 benchmarks (MMLU, SimpleQA). Both models are evenly matched across the benchmarks.
On price, Qwen3 VL 235B A22B Thinking is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 235B A22B Thinking also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose o3-mini
- you want predictable pricing at $1.10/M input and $4.40/M output
Choose Qwen3 VL 235B A22B Thinking
- cost matters — it's about 1.6x 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
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
o3-mini outperforms in 2 benchmarks (IFEval, Multi-IF), while Qwen3 VL 235B A22B Thinking is better at 2 benchmarks (MMLU, SimpleQA).
Both models are evenly matched across the benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, o3-mini ($1.10/1M tokens) is 2.4x more expensive than Qwen3 VL 235B A22B Thinking ($0.45/1M tokens).
For output processing, o3-mini ($4.40/1M tokens) is 1.3x more expensive than Qwen3 VL 235B A22B Thinking ($3.49/1M tokens).
In conclusion, o3-mini is more expensive than Qwen3 VL 235B A22B Thinking.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3 VL 235B A22B Thinking accepts 262,144 input tokens compared to o3-mini's 200,000 tokens. Qwen3 VL 235B A22B Thinking can generate longer responses up to 262,144 tokens, while o3-mini is limited to 100,000 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 235B A22B Thinking supports multimodal inputs, whereas o3-mini does not.
Qwen3 VL 235B A22B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
o3-mini
Qwen3 VL 235B A22B Thinking
License
Usage and distribution terms
o3-mini is licensed under a proprietary license, while Qwen3 VL 235B A22B Thinking 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
o3-mini was released on 2025-01-30, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.
Qwen3 VL 235B A22B Thinking is 8 months newer than o3-mini.
Jan 30, 2025
1.6 years ago
Sep 22, 2025
11 months ago
7mo newerKnowledge Cutoff
When training data ends
o3-mini has a documented knowledge cutoff of 2023-09-30, while Qwen3 VL 235B A22B Thinking's cutoff date is not specified.
We can confirm o3-mini's training data extends to 2023-09-30, but cannot make a direct comparison without Qwen3 VL 235B A22B Thinking's cutoff date.
Sep 2023
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Provider Availability
o3-mini is available from Azure, OpenAI. Qwen3 VL 235B A22B Thinking is available from DeepInfra, Novita.
o3-mini
Qwen3 VL 235B A22B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against o3-mini and Qwen3 VL 235B A22B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about o3-mini vs Qwen3 VL 235B A22B Thinking.