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GPT-4o vs Qwen3 VL 32B Thinking

Qwen3 VL 32B Thinking leads the LLM Stats Score 23.5 to 11.6.

OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3 VL 32B Thinking leads the overall LLM Stats Score 23.5 to 11.6, ranking #166 overall.

In the 3 individual benchmarks reported for both models, Qwen3 VL 32B Thinking wins 3; 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 GPT-4o

  • you want predictable pricing at $2.50/M input and $10.00/M output

Choose Qwen3 VL 32B Thinking

  • overall performance matters — it scores 23.5 and ranks #166 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 3 exact shared results
  • 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
11.6
#246
23.5
#166
12.3
#234
24.7
#145
Cost, coverage & limits
Benchmark wins
0 of 3
3 of 3
Input price
$2.50 / M
— / M
Output price
$10.00 / M
— / M
Context window
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
GPT-4o
Qwen3 VL 32B Thinking
18.3#173
25.5#103
18.8#87
28.1#33
18.8#74
27.5#26
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

8 reported for GPT-4o · 47 for Qwen3 VL 32B Thinking

3 shared

GPT-4o outperforms in 0 benchmarks, while Qwen3 VL 32B Thinking is better at 2 benchmarks (GPQA, MMLU-Pro).

Qwen3 VL 32B Thinking shows notably better performance in the majority of benchmarks.

Fri Sep 04 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only GPT-4o specifies input context (128,000 tokens). Only GPT-4o specifies output context (4,096 tokens).

OpenAI
GPT-4o
Input128,000 tokens
Output4,096 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Thinking
Input- tokens
Output- tokens
Fri Sep 04 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GPT-4o and Qwen3 VL 32B Thinking support multimodal inputs.

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

GPT-4o

Text
Images
Audio
Video

Qwen3 VL 32B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4o is licensed under a proprietary license, while Qwen3 VL 32B Thinking uses Apache 2.0.

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

GPT-4o

Proprietary

Closed source

Qwen3 VL 32B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-4o was released on 2024-05-13, while Qwen3 VL 32B Thinking was released on 2025-09-22.

Qwen3 VL 32B Thinking is 17 months newer than GPT-4o.

GPT-4o

May 13, 2024

2.3 years ago

Qwen3 VL 32B Thinking

Sep 22, 2025

11 months ago

1.4yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GPT-4o and Qwen3 VL 32B Thinking side-by-side, then vote on the output you prefer.

GPT-4o
✓ Preferred
Qwen3 VL 32B Thinking
Open in Playground

FAQ

Common questions about GPT-4o vs Qwen3 VL 32B Thinking.

Which is better, GPT-4o or Qwen3 VL 32B Thinking?

Qwen3 VL 32B Thinking leads the LLM Stats Score 23.5 to 11.6. GPT-4o is made by OpenAI and Qwen3 VL 32B 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 GPT-4o compare to Qwen3 VL 32B Thinking in benchmarks?

GPT-4o scores MGSM: 90.5%, HumanEval: 90.2%, MMLU: 88.7%, DROP: 83.4%, MATH: 76.6%. Qwen3 VL 32B Thinking scores DocVQAtest: 96.1%, ScreenSpot: 95.7%, MMLU-Redux: 91.9%, MMBench-V1.1: 90.8%, CharXiv-D: 90.2%.

What are the context window sizes for GPT-4o and Qwen3 VL 32B Thinking?

GPT-4o supports 128K tokens and Qwen3 VL 32B Thinking supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-4o and Qwen3 VL 32B Thinking?

Key differences include LLM Stats Score (11.6 vs 23.5), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-4o and Qwen3 VL 32B Thinking?

GPT-4o is developed by OpenAI and Qwen3 VL 32B Thinking is developed by Alibaba Cloud / Qwen Team.