Activefastmultimodal Open Source

Qwen2.5-VL 3B

by Alibaba· Released January 2025

Qwen2.5-VL 3B is a compact multimodal vision-language model from Alibaba's Qwen series, designed for efficient image and video understanding. It excels in tasks like visual question answering, document parsing, and video analysis while maintaining a small footprint for deployment on edge devices.

Official Site 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

128K tokens

Max output

—

Modalities

textimagevideo

Parameters

License

Apache-2.0

Capabilities

Vision understandingVideo understandingDocument parsingFunction CallingCode GenerationStreamingJSON Mode

Best For

Efficient multimodal tasks requiring vision-language understanding on resource-constrained devices.

Strengths

Strong performance on visual reasoning benchmarks despite small size
Supports dynamic resolution and multi-frame video input
Efficient for deployment on edge devices and mobile platforms

Limitations

Smaller parameter count limits complex reasoning compared to larger models
May struggle with highly specialized or niche visual domains
Limited to text and image/video modalities; no native audio support

Use Cases

Visual question answering on mobile apps

Document and receipt parsing for business automation

Video content summarization and analysis

Assistive technology for visually impaired users

E-commerce product image understanding

Educational tools for interactive learning

Real-time video surveillance analysis

Improvements Over Previous Model

Introduced as a new smaller variant in the Qwen2.5-VL family, offering a 3B parameter option for efficient deployment
Supports dynamic resolution and multi-frame video input, improving over previous Qwen-VL models
Enhanced visual understanding capabilities with better performance on benchmarks like DocVQA and ChartQA
Improved multilingual support for both text and vision tasks

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Activefastmultimodal Open Source

Qwen2.5-VL 3B

by Alibaba· Released January 2025

Official Site 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

128K tokens

Max output

—

Modalities

textimagevideo

Parameters

License

Apache-2.0

Capabilities

Vision understandingVideo understandingDocument parsingFunction CallingCode GenerationStreamingJSON Mode

Best For

Efficient multimodal tasks requiring vision-language understanding on resource-constrained devices.

Strengths

Strong performance on visual reasoning benchmarks despite small size
Supports dynamic resolution and multi-frame video input
Efficient for deployment on edge devices and mobile platforms

Limitations

Smaller parameter count limits complex reasoning compared to larger models
May struggle with highly specialized or niche visual domains
Limited to text and image/video modalities; no native audio support

Use Cases

Visual question answering on mobile apps

Document and receipt parsing for business automation

Video content summarization and analysis

Assistive technology for visually impaired users

E-commerce product image understanding

Educational tools for interactive learning

Real-time video surveillance analysis

Improvements Over Previous Model

Introduced as a new smaller variant in the Qwen2.5-VL family, offering a 3B parameter option for efficient deployment
Supports dynamic resolution and multi-frame video input, improving over previous Qwen-VL models
Enhanced visual understanding capabilities with better performance on benchmarks like DocVQA and ChartQA
Improved multilingual support for both text and vision tasks

Back to all models