o3-pro vs Qwen3 VL 4B Instruct
Comparing o3-pro and Qwen3 VL 4B Instruct across benchmarks, pricing, and capabilities.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
o3-pro and Qwen3 VL 4B Instruct trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Qwen3 VL 4B Instruct is roughly 155.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 4B Instruct also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose o3-pro
- you want predictable pricing at $20.00/M input and $80.00/M output
Choose Qwen3 VL 4B Instruct
- cost matters — it's about 155.6x 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.
Individual benchmarks
0 reported for o3-pro · 45 for Qwen3 VL 4B Instruct
o3-pro and Qwen3 VL 4B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, o3-pro ($20.00/1M tokens) is 200.0x more expensive than Qwen3 VL 4B Instruct ($0.10/1M tokens).
For output processing, o3-pro ($80.00/1M tokens) is 133.3x more expensive than Qwen3 VL 4B Instruct ($0.60/1M tokens).
In conclusion, o3-pro is more expensive than Qwen3 VL 4B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3 VL 4B Instruct accepts 262,144 input tokens compared to o3-pro's 200,000 tokens. Qwen3 VL 4B Instruct can generate longer responses up to 262,144 tokens, while o3-pro is limited to 100,000 tokens.
Input capabilities
Documented input modalities across available providers
Both o3-pro and Qwen3 VL 4B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
o3-pro
Qwen3 VL 4B Instruct
License
Usage and distribution terms
o3-pro is licensed under a proprietary license, while Qwen3 VL 4B 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
o3-pro was released on 2025-06-10, while Qwen3 VL 4B Instruct was released on 2025-09-22.
Qwen3 VL 4B Instruct is 3 months newer than o3-pro.
Jun 10, 2025
1.3 years ago
Sep 22, 2025
11 months ago
3mo newerKnowledge Cutoff
When training data ends
o3-pro has a documented knowledge cutoff of 2024-05-31, while Qwen3 VL 4B Instruct's cutoff date is not specified.
We can confirm o3-pro's training data extends to 2024-05-31, but cannot make a direct comparison without Qwen3 VL 4B Instruct's cutoff date.
May 2024
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Provider Availability
o3-pro is available from OpenAI. Qwen3 VL 4B Instruct is available from DeepInfra.
o3-pro
Qwen3 VL 4B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against o3-pro and Qwen3 VL 4B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about o3-pro vs Qwen3 VL 4B Instruct.