Model Comparison

GPT-4.1 nano vs Qwen2.5 VL 32B Instruct

GPT-4.1 nano shows notably better performance in the majority of benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

GPT-4.1 nano outperforms in 2 benchmarks (GPQA, MMLU), while Qwen2.5 VL 32B Instruct is better at 1 benchmark (MMMU).

GPT-4.1 nano shows notably better performance in the majority of benchmarks.

Tue May 26 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only GPT-4.1 nano specifies input context (1,047,576 tokens). Only GPT-4.1 nano specifies output context (32,768 tokens).

GPT-4.1 nano

Input1,047,576 tokens

Output32,768 tokens

Qwen2.5 VL 32B Instruct

Input- tokens

Output- tokens

Tue May 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both GPT-4.1 nano and Qwen2.5 VL 32B Instruct support multimodal inputs.

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

GPT-4.1 nano

Text

Images

Audio

Video

Qwen2.5 VL 32B Instruct

Text

Images

Audio

Video

License

Usage and distribution terms

GPT-4.1 nano is licensed under a proprietary license, while Qwen2.5 VL 32B Instruct uses Apache 2.0.

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

GPT-4.1 nano

Proprietary

Closed source

Qwen2.5 VL 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-4.1 nano was released on 2025-04-14, while Qwen2.5 VL 32B Instruct was released on 2025-02-28.

GPT-4.1 nano is 2 months newer than Qwen2.5 VL 32B Instruct.

GPT-4.1 nano

Apr 14, 2025

1.1 years ago

1mo newer

Qwen2.5 VL 32B Instruct

Feb 28, 2025

1.2 years ago

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Qwen2.5 VL 32B Instruct's cutoff date is not specified.

We can confirm GPT-4.1 nano's training data extends to 2024-05-31, but cannot make a direct comparison without Qwen2.5 VL 32B Instruct's cutoff date.

GPT-4.1 nano

May 2024

Qwen2.5 VL 32B Instruct

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Outputs Comparison

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Key Takeaways

GPT-4.1 nano

View details

OpenAI

Larger context window (1,047,576 tokens)

Higher GPQA score (50.3% vs 46.0%)

Higher MMLU score (80.1% vs 78.4%)

Qwen2.5 VL 32B Instruct

View details

Alibaba Cloud / Qwen Team

Has open weights

Higher MMMU score (70.0% vs 55.4%)

Detailed Comparison

AI Model Comparison Table
Feature	GPT-4.1 nano	Qwen2.5 VL 32B Instruct

FAQ

Common questions about GPT-4.1 nano vs Qwen2.5 VL 32B Instruct.

Which is better, GPT-4.1 nano or Qwen2.5 VL 32B Instruct?

GPT-4.1 nano shows notably better performance in the majority of benchmarks. GPT-4.1 nano is made by OpenAI and Qwen2.5 VL 32B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GPT-4.1 nano compare to Qwen2.5 VL 32B Instruct in benchmarks?

GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%. Qwen2.5 VL 32B Instruct scores DocVQA: 94.8%, Android Control Low_EM: 93.3%, HumanEval: 91.5%, ScreenSpot: 88.5%, MBPP: 84.0%.

What are the context window sizes for GPT-4.1 nano and Qwen2.5 VL 32B Instruct?

GPT-4.1 nano supports 1.0M tokens and Qwen2.5 VL 32B Instruct 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-4.1 nano and Qwen2.5 VL 32B Instruct?

Key differences include licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-4.1 nano and Qwen2.5 VL 32B Instruct?

GPT-4.1 nano is developed by OpenAI and Qwen2.5 VL 32B Instruct is developed by Alibaba Cloud / Qwen Team.