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GPT-4.1 nano vs Qwen2.5 32B Instruct

Qwen2.5 32B Instruct leads the LLM Stats Score 7.8 to 1.9.

OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen2.5 32B Instruct leads the overall LLM Stats Score 7.8 to 1.9, ranking #273 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-4.1 nano

  • you want the most recent training data — it shipped Apr 2025

Choose Qwen2.5 32B Instruct

  • overall performance matters — it scores 7.8 and ranks #273 on LLM Stats
  • your work emphasizes coding — it leads those capability indexes
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Core performance indexes
1.9
#308
7.8
#273
2.2
#295
7.3
#271
-11.7
#257
9.5
#164
Cost, coverage & limits
Benchmark wins
1 of 2
1 of 2
Input price
$0.10 / M
— / M
Output price
$0.40 / M
— / M
Context window
1,047,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GPT-4.1 nano
Qwen2.5 32B Instruct
5.3#268
16.7#194
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

24 reported for GPT-4.1 nano · 18 for Qwen2.5 32B Instruct

2 shared

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

Both models are evenly matched across the 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-4.1 nano specifies input context (1,047,576 tokens). Only GPT-4.1 nano specifies output context (32,768 tokens).

OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 32B Instruct
Input- tokens
Output- tokens
Fri Sep 04 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GPT-4.1 nano supports multimodal inputs, whereas Qwen2.5 32B Instruct does not.

GPT-4.1 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-4.1 nano

Text
Images
Audio
Video

Qwen2.5 32B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4.1 nano is licensed under a proprietary license, while Qwen2.5 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 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 32B Instruct was released on 2024-09-19.

GPT-4.1 nano is 7 months newer than Qwen2.5 32B Instruct.

GPT-4.1 nano

Apr 14, 2025

1.4 years ago

6mo newer
Qwen2.5 32B Instruct

Sep 19, 2024

2.0 years ago

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Qwen2.5 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 32B Instruct's cutoff date.

GPT-4.1 nano

May 2024

Qwen2.5 32B Instruct

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GPT-4.1 nano and Qwen2.5 32B Instruct side-by-side, then vote on the output you prefer.

GPT-4.1 nano
✓ Preferred
Qwen2.5 32B Instruct
Open in Playground

FAQ

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

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

Qwen2.5 32B Instruct leads the LLM Stats Score 7.8 to 1.9. GPT-4.1 nano is made by OpenAI and Qwen2.5 32B Instruct 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-4.1 nano compare to Qwen2.5 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 32B Instruct scores GSM8k: 95.9%, HumanEval: 88.4%, HellaSwag: 85.2%, BBH: 84.5%, MBPP: 84.0%.

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

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

Key differences include LLM Stats Score (1.9 vs 7.8), multimodal support (yes vs no), 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 32B Instruct?

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