Text Generation Model

Llama 3.2 11B Instruct

Advanced state-of-the-art small language model with language understanding, superior reasoning, and text generation.

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Publisher

Multilingual instruction-tuned language model from Meta

Llama 3.2 11B Instruct is a multilingual large language model developed by Meta, part of the Llama 3.2 collection of pretrained and instruction-tuned generative models. It uses an optimized transformer architecture and has been fine-tuned with supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety. The model accepts text input and produces text output, supporting a context window of 128,000 tokens.

This model is optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks. It is instruction-tuned, meaning it is designed to follow natural language instructions across a range of tasks such as question answering, text generation, and reasoning. The 11B parameter size positions it as a mid-range model within the Llama 3.2 family, which also includes 1B and 3B text-only variants.

Capabilities

What Llama 3.2 11B Instruct supports

Multilingual Dialogue

Handles conversational tasks across multiple languages, optimized specifically for instruction-following in multilingual settings.

Long Context Processing

Processes inputs and outputs within a 128,000-token context window, enabling handling of long documents or extended conversations.

Agentic Retrieval

Supports agentic workflows where the model retrieves and synthesizes information across multi-step tasks.

Text Summarization

Condenses long-form content into concise summaries, a use case explicitly highlighted in Meta's model documentation.

Instruction Following

Fine-tuned with SFT and RLHF to follow natural language instructions accurately across a variety of task types.

Text Reasoning

Applies multi-step reasoning to answer questions and solve problems presented in natural language prompts.

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FAQ

Common questions about Llama 3.2 11B Instruct

What is the context window for Llama 3.2 11B Instruct?

The model supports a context window of 128,000 tokens, allowing it to process long documents or extended multi-turn conversations in a single request.

What languages does this model support?

Llama 3.2 11B Instruct is designed for multilingual use cases. Meta's documentation highlights its optimization for multilingual dialogue, though specific supported languages are detailed in Meta's official model card.

How was this model trained and aligned?

The model uses an optimized transformer architecture and was fine-tuned using supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.

What is this model best suited for?

According to Meta, Llama 3.2 11B Instruct is optimized for multilingual dialogue, agentic retrieval, and summarization tasks. It is an instruction-tuned model, making it well-suited for conversational and task-following applications.

Is a training data cutoff date available for this model?

A specific training data cutoff date is not provided in the available metadata for this model. Refer to Meta's official model card for the most accurate information on training data.

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