Model Comparison

GPT-4.1 nano vs Qwen2.5-Omni-7B

Qwen2.5-Omni-7B 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 1 benchmarks (GPQA), while Qwen2.5-Omni-7B is better at 2 benchmarks (MathVista, MMMU).

Qwen2.5-Omni-7B shows notably better performance in the majority of benchmarks.

Sat Apr 11 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sat Apr 11 2026 • llm-stats.com
OpenAI
GPT-4.1 nano
Input tokens$0.10
Output tokens$0.40
Best providerOpenAI
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

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-Omni-7B
Input- tokens
Output- tokens
Sat Apr 11 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both GPT-4.1 nano and Qwen2.5-Omni-7B 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-Omni-7B

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4.1 nano is licensed under a proprietary license, while Qwen2.5-Omni-7B 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-Omni-7B

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-Omni-7B was released on 2025-03-27.

GPT-4.1 nano is 1 month newer than Qwen2.5-Omni-7B.

GPT-4.1 nano

Apr 14, 2025

12 months ago

2w newer
Qwen2.5-Omni-7B

Mar 27, 2025

1.0 years ago

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Qwen2.5-Omni-7B'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-Omni-7B's cutoff date.

GPT-4.1 nano

May 2024

Qwen2.5-Omni-7B

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Outputs Comparison

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Key Takeaways

OpenAI
Larger context window (1,047,576 tokens)
Higher GPQA score (50.3% vs 30.8%)
Alibaba Cloud / Qwen Team

Qwen2.5-Omni-7B

View details

Alibaba Cloud / Qwen Team

Has open weights
Higher MathVista score (67.9% vs 56.2%)
Higher MMMU score (59.2% vs 55.4%)

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT-4.1 nano
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B

FAQ

Common questions about GPT-4.1 nano vs Qwen2.5-Omni-7B

Qwen2.5-Omni-7B shows notably better performance in the majority of benchmarks. GPT-4.1 nano is made by OpenAI and Qwen2.5-Omni-7B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%. Qwen2.5-Omni-7B scores DocVQA: 95.2%, VocalSound: 93.9%, GSM8k: 88.7%, GiantSteps Tempo: 88.0%, ChartQA: 85.3%.
GPT-4.1 nano supports 1.0M tokens and Qwen2.5-Omni-7B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
GPT-4.1 nano is developed by OpenAI and Qwen2.5-Omni-7B is developed by Alibaba Cloud / Qwen Team.