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Available now on ModelsLab · Language Model

Meta: Llama 3.2 3B InstructCompact. Multilingual. Instruct.

Try Meta: Llama 3.2 3B InstructAPI Documentation

Deploy Efficiently. Scale Smart.

128k Context

Process Long Inputs

Handle extended conversations and documents with 128k token context window.

Multilingual Support

Eight Languages Covered

Generate text in English, German, French, Italian, Portuguese, Hindi, Spanish, Thai.

Low Latency

Run On Edge Devices

Optimize Meta: Llama 3.2 3B Instruct for mobile assistants and real-time inference.

Examples

See what Meta: Llama 3.2 3B Instruct can create

Copy any prompt below and try it yourself in the playground.

Code Review

“<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are a helpful code reviewer.<|eot_id|><|start_header_id|>user<|end_header_id|>Review this Python function for errors and suggest improvements: def factorial(n): if n == 0: return 1 else: return n * factorial(n-1)<|eot_id|><|start_header_id|>assistant<|end_header_id|>”

Text Summary

“<|begin_of_text|><|start_header_id|>system<|end_header_id|>Summarize articles concisely.<|eot_id|><|start_header_id|>user<|end_header_id|>Summarize key points from this climate change report excerpt: [insert long excerpt here]<|eot_id|><|start_header_id|>assistant<|end_header_id|>”

Query Rewrite

“<|begin_of_text|><|start_header_id|>system<|end_header_id|>Rewrite prompts for clarity.<|eot_id|><|start_header_id|>user<|end_header_id|>Rewrite this search query to be more precise: best laptops under 1000 dollars<|eot_id|><|start_header_id|>assistant<|end_header_id|>”

Translation Task

“<|begin_of_text|><|start_header_id|>system<|end_header_id|>Translate accurately between languages.<|eot_id|><|start_header_id|>user<|end_header_id|>Translate to German: The quick brown fox jumps over the lazy dog.<|eot_id|><|start_header_id|>assistant<|end_header_id|>”

For Developers

A few lines of code.
Instruct model. One call.

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

  • Serverless: scales to zero, scales to millions
  • Pay per token, no minimums
  • Python and JavaScript SDKs, plus REST API
API Documentation 
import requests


response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

FAQ

Common questions about Meta: Llama 3.2 3B Instruct

Read the docs

Meta: Llama 3.2 3B Instruct is a 3B parameter instruction-tuned LLM for text generation. It supports multilingual dialogue and agentic tasks. Use Meta: Llama 3.2 3B Instruct API for low-latency inference.

Meta llama 3.2 3b instruct handles 128k tokens. This enables long-form processing. Knowledge cutoff is December 2023.

Yes, Meta: Llama 3.2 3B Instruct model is licensed for commercial use. It excels in chat and summarization. Deploy via API endpoints.

Outputs around 53.7 tokens per second on average. Suitable for edge devices. Quantized versions reduce memory use.

Ideal for summarization, translation, classification. Powers writing assistants and query rewriting. Outperforms similar open models on benchmarks.

Available through LLM endpoints like ModelsLab API. Supports text-in text-out. Fine-tuned with SFT and RLHF.

Ready to create?

Start generating with Meta: Llama 3.2 3B Instruct on ModelsLab.

Try Meta: Llama 3.2 3B InstructAPI Documentation