Activefastmultimodal Open Source

Llama 4 Scout

by Meta· Released April 2025· Cutoff December 2024

Llama 4 Scout is a lightweight, efficient multimodal model from Meta, designed for fast inference and on-device deployment. It supports text and image inputs, making it suitable for vision-language tasks. As part of the Llama 4 family, Scout balances performance with resource efficiency.

Official Site API Docs 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

1M tokens

Max output

—

Modalities

textimage

Parameters

17B

License

Llama 4 Community License

Capabilities

VisionImage UnderstandingText GenerationMultimodal ReasoningCode GenerationFunction CallingStreaming

Best For

Efficient multimodal tasks requiring fast inference and low resource usage, including on-device applications.

Strengths

Extremely large context window (1M tokens)
Fast inference speed
Open source and free to use
Strong vision-language capabilities
Efficient for deployment on consumer hardware

Limitations

Smaller parameter count may limit complex reasoning compared to larger models
Not as strong in pure text-only tasks as larger Llama 4 variants
Limited to text and image modalities (no audio/video)
Newer model with less community adoption and tooling

Use Cases

Image captioning and visual question answering

Document analysis with long context

On-device AI assistants with vision

Code generation from screenshots

Multimodal chatbots

Content moderation with image understanding

Educational tools combining text and images

Improvements Over Previous Model

First model in the Llama 4 family, so no direct predecessor; introduces MoE architecture with 17B active parameters
Context window of 1M tokens, significantly larger than Llama 3's 128K
Native multimodal support (text+image) unlike Llama 3 which was text-only
Open source under Llama 4 Community License, continuing Meta's open approach
Optimized for fast inference and on-device deployment

Back to all models

Activefastmultimodal Open Source

Llama 4 Scout

by Meta· Released April 2025· Cutoff December 2024

Official Site API Docs 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

1M tokens

Max output

—

Modalities

textimage

Parameters

17B

License

Llama 4 Community License

Capabilities

VisionImage UnderstandingText GenerationMultimodal ReasoningCode GenerationFunction CallingStreaming

Best For

Efficient multimodal tasks requiring fast inference and low resource usage, including on-device applications.

Strengths

Extremely large context window (1M tokens)
Fast inference speed
Open source and free to use
Strong vision-language capabilities
Efficient for deployment on consumer hardware

Limitations

Smaller parameter count may limit complex reasoning compared to larger models
Not as strong in pure text-only tasks as larger Llama 4 variants
Limited to text and image modalities (no audio/video)
Newer model with less community adoption and tooling

Use Cases

Image captioning and visual question answering

Document analysis with long context

On-device AI assistants with vision

Code generation from screenshots

Multimodal chatbots

Content moderation with image understanding

Educational tools combining text and images

Improvements Over Previous Model

First model in the Llama 4 family, so no direct predecessor; introduces MoE architecture with 17B active parameters
Context window of 1M tokens, significantly larger than Llama 3's 128K
Native multimodal support (text+image) unlike Llama 3 which was text-only
Open source under Llama 4 Community License, continuing Meta's open approach
Optimized for fast inference and on-device deployment

Back to all models