Activefastllm Open Source

Llama 3.2 3B

by Meta· Released September 2024· Cutoff December 2023

Llama 3.2 3B is a lightweight, multilingual text-only model from Meta, optimized for on-device and edge applications. It is part of the Llama 3.2 family, which includes both text-only and vision models, and offers strong performance for its size with support for 8 languages.

Official Site API Docs 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

128K tokens

Max output

—

Modalities

text

Parameters

License

Llama 3.2 Community License

Capabilities

Text GenerationMultilingualFunction CallingCode GenerationStreamingJSON Mode

Best For

On-device and edge applications requiring efficient, low-latency text generation in multiple languages.

Strengths

Lightweight and efficient for deployment on mobile and edge devices
Supports 8 languages (English, German, French, Italian, Portuguese, Hindi, Spanish, Thai)
128K token context window for long-form tasks
Strong performance on reasoning and coding benchmarks for its size

Limitations

Text-only model, no vision or multimodal capabilities
Smaller parameter count limits complex reasoning compared to larger models
May not match the accuracy of larger Llama models on specialized tasks
Limited to 8 languages, not fully multilingual

Use Cases

On-device chatbots and virtual assistants

Real-time text translation and summarization

Edge-based code generation and completion

Privacy-sensitive applications requiring local processing

Educational tools and language learning apps

Customer support automation on mobile devices

Content generation for social media and messaging

Improvements Over Previous Model

Introduced as a new smaller model in the Llama 3.2 family, offering a lightweight alternative to larger models
Supports 128K token context window, matching larger Llama 3.1 models
Multilingual support for 8 languages, expanding beyond English-only predecessors
Optimized for on-device deployment with reduced memory footprint
Improved efficiency and speed for edge applications

Back to all models

Use Cases

On-device chatbots and virtual assistants

Real-time text translation and summarization

Edge-based code generation and completion

Privacy-sensitive applications requiring local processing

Educational tools and language learning apps

Customer support automation on mobile devices

Content generation for social media and messaging

Improvements Over Previous Model

Introduced as a new smaller model in the Llama 3.2 family, offering a lightweight alternative to larger models

Supports 128K token context window, matching larger Llama 3.1 models

Multilingual support for 8 languages, expanding beyond English-only predecessors

Optimized for on-device deployment with reduced memory footprint

Improved efficiency and speed for edge applications