GPT-5.4 nano vs Qwen3 VL 32B Thinking

Q: What are the context window sizes for GPT-5.4 nano and Qwen3 VL 32B Thinking?

GPT-5.4 nano supports 400K 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.

Q: What are the main differences between GPT-5.4 nano and Qwen3 VL 32B Thinking?

Key differences include LLM Stats Score (26.6 vs 23.6), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Q: Who makes GPT-5.4 nano and Qwen3 VL 32B Thinking?

GPT-5.4 nano is developed by OpenAI and Qwen3 VL 32B Thinking is developed by Alibaba Cloud / Qwen Team.

GPT-5.4 nano leads the LLM Stats Score 26.6 to 23.6.

OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

GPT-5.4 nano leads the overall LLM Stats Score 26.6 to 23.6, ranking #150 overall.

The models split the 2 individual benchmarks reported for both models evenly.

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

Choose GPT-5.4 nano

overall performance matters — it scores 26.6 and ranks #150 on LLM Stats
you want the most recent training data — it shipped Mar 2026

Choose Qwen3 VL 32B Thinking

you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

GPT-5.4 nano

OpenAI

Qwen3 VL 32B Thinking

Alibaba Cloud / Qwen Team

Core performance indexes

LLM Stats Score

26.6

#150 · 21 evals

Best

23.6

#174 · 47 evals

Reasoning

27.5

#136 · 17 evals

Best

24.7

#154 · 28 evals

Agents

11.0

#112 · 6 evals

12.9

#97 · 3 evals

Best

Cost, coverage & limits

Benchmark wins

1 of 2

Input price

$0.20 / M

— / M

Output price

$1.25 / M

— / M

Context window

400,000

—

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared

Index

GPT-5.4 nano

Qwen3 VL 32B Thinking

Math

21.5#145 · 2 evals

25.4#111 · 10 evals

Vision

9.5#125 · 6 evals

16.9#85 · 28 evals

Multimodal

11.0#112 · 4 evals

19.5#72 · 24 evals

Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for GPT-5.4 nano · 47 for Qwen3 VL 32B Thinking

2 shared

GPT-5.4 nano outperforms in 1 benchmarks (GPQA), while Qwen3 VL 32B Thinking is better at 1 benchmark (MMMU-Pro).

Both models are evenly matched across the benchmarks.

Sun Sep 20 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-5.4 nano specifies input context (400,000 tokens). Only GPT-5.4 nano specifies output context (128,000 tokens).

GPT-5.4 nano

Input400,000 tokens

Output128,000 tokens

Qwen3 VL 32B Thinking

Input- tokens

Output- tokens

Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GPT-5.4 nano and Qwen3 VL 32B Thinking support multimodal inputs.

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

GPT-5.4 nano

Text

Images

Audio

Video

Qwen3 VL 32B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

GPT-5.4 nano 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-5.4 nano

Proprietary

Closed source

Qwen3 VL 32B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-5.4 nano was released on 2026-03-17, while Qwen3 VL 32B Thinking was released on 2025-09-22.

GPT-5.4 nano is 6 months newer than Qwen3 VL 32B Thinking.

GPT-5.4 nano

Mar 17, 2026

6 months ago

5mo newer

Qwen3 VL 32B Thinking

Sep 22, 2025

12 months ago

Knowledge Cutoff

When training data ends

GPT-5.4 nano has a documented knowledge cutoff of 2025-08-31, while Qwen3 VL 32B Thinking's cutoff date is not specified.

We can confirm GPT-5.4 nano's training data extends to 2025-08-31, but cannot make a direct comparison without Qwen3 VL 32B Thinking's cutoff date.

GPT-5.4 nano

Aug 2025

Qwen3 VL 32B Thinking

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GPT-5.4 nano and Qwen3 VL 32B Thinking side-by-side, then vote on the output you prefer.

GPT-5.4 nano

✓ Preferred

Qwen3 VL 32B Thinking

Open in Playground

FAQ

Common questions about GPT-5.4 nano vs Qwen3 VL 32B Thinking.

Which is better, GPT-5.4 nano or Qwen3 VL 32B Thinking?

GPT-5.4 nano leads the LLM Stats Score 26.6 to 23.6. GPT-5.4 nano 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-5.4 nano compare to Qwen3 VL 32B Thinking in benchmarks?

GPT-5.4 nano scores Tau2 Telecom: 92.5%, GPQA: 82.8%, OmniDocBench 1.5: 75.8%, Graphwalks BFS <128k: 73.4%, LiveBench: 70.1%. 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-5.4 nano and Qwen3 VL 32B Thinking?

GPT-5.4 nano supports 400K 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-5.4 nano and Qwen3 VL 32B Thinking?

Key differences include LLM Stats Score (26.6 vs 23.6), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-5.4 nano and Qwen3 VL 32B Thinking?

GPT-5.4 nano is developed by OpenAI and Qwen3 VL 32B Thinking is developed by Alibaba Cloud / Qwen Team.

GPT-5.4 nano vs Qwen3 VL 32B Thinking