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o1-pro vs Qwen3 VL 4B Thinking

o1-pro leads the LLM Stats Score 19.7 to 12.9.

OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

o1-pro leads the overall LLM Stats Score 19.7 to 12.9, ranking #199 overall.

In the 1 individual benchmarks reported for both models, o1-pro wins 1; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose o1-pro

  • overall performance matters — it scores 19.7 and ranks #199 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results

Choose Qwen3 VL 4B Thinking

  • 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.

Core performance indexes
19.7
#199
12.9
#248
20.0
#189
14.0
#230
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
— / M
$0.10 / M
Output price
— / M
$1.00 / M
Context window
262,144

Individual benchmarks

2 reported for o1-pro · 48 for Qwen3 VL 4B Thinking

1 shared

o1-pro outperforms in 1 benchmarks (GPQA), while Qwen3 VL 4B Thinking is better at 0 benchmarks.

o1-pro significantly outperforms across most benchmarks.

Sun Sep 13 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Qwen3 VL 4B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 4B Thinking specifies output context (262,144 tokens).

OpenAI
o1-pro
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Sun Sep 13 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both o1-pro and Qwen3 VL 4B Thinking support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

o1-pro

Text
Images
Audio
Video

Qwen3 VL 4B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

o1-pro is licensed under a proprietary license, while Qwen3 VL 4B Thinking uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

o1-pro

Proprietary

Closed source

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

o1-pro was released on 2024-12-17, while Qwen3 VL 4B Thinking was released on 2025-09-22.

Qwen3 VL 4B Thinking is 9 months newer than o1-pro.

o1-pro

Dec 17, 2024

1.7 years ago

Qwen3 VL 4B Thinking

Sep 22, 2025

11 months ago

9mo newer

Knowledge Cutoff

When training data ends

o1-pro has a documented knowledge cutoff of 2023-09-30, while Qwen3 VL 4B Thinking's cutoff date is not specified.

We can confirm o1-pro's training data extends to 2023-09-30, but cannot make a direct comparison without Qwen3 VL 4B Thinking's cutoff date.

o1-pro

Sep 2023

Qwen3 VL 4B Thinking

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against o1-pro and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.

o1-pro
✓ Preferred
Qwen3 VL 4B Thinking
Open in Playground

FAQ

Common questions about o1-pro vs Qwen3 VL 4B Thinking.

Which is better, o1-pro or Qwen3 VL 4B Thinking?

o1-pro leads the LLM Stats Score 19.7 to 12.9. o1-pro is made by OpenAI and Qwen3 VL 4B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does o1-pro compare to Qwen3 VL 4B Thinking in benchmarks?

o1-pro scores AIME 2024: 86.0%, GPQA: 79.0%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

What are the context window sizes for o1-pro and Qwen3 VL 4B Thinking?

o1-pro supports an unknown number of tokens and Qwen3 VL 4B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between o1-pro and Qwen3 VL 4B Thinking?

Key differences include LLM Stats Score (19.7 vs 12.9), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes o1-pro and Qwen3 VL 4B Thinking?

o1-pro is developed by OpenAI and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.