NLP

CORE MACHINE LEARNING

Llama Guard 3-1B-INT4: Compact and Efficient Safeguard for Human-AI Conversations

November 20, 2024

Abstract

This paper presents Llama Guard 3-1B-INT4, a compact and efficient Llama Guard model, which has been open-sourced to the community during Meta Connect 2024. We demonstrate that Llama Guard 3-1B-INT4 can be deployed on resource-constrained devices, achieving a throughput of at least 30 tokens per second and a time-to-first-token of 2.5 seconds or less on a commodity Android mobile CPU. Notably, our experiments show that Llama Guard 3-1B-INT4 attains comparable or superior safety moderation scores to its larger counterpart, Llama Guard 3-1B, despite being approximately 7 times smaller in size (440MB).

Download the Paper

AUTHORS

Written by

Igor Fedorov

Kate Plawiak

Lemeng Wu

Tarek Elgamal

Naveen Suda

Eric Smith

Hongyuan Zhan

Jianfeng Chi

Yuriy Hulovatyy

Kimish Patel

Zechun Liu

Yangyang Shi

Tijmen Blankevoort

Mahesh Pasupuleti

Bilge Soran

Zacharie Delpierre Coudert

Rachad Alao

Raghuraman Krishnamoorthi

Vikas Chandra

Publisher

arXiv

Research Topics

Natural Language Processing (NLP)

Core Machine Learning

Related Publications

September 24, 2026

REINFORCEMENT LEARNING

RESEARCH

MaD-RL: Matching Distributions for Calibrating LLMs with Reinforcement Learning

Sourabh Kulkarni, Ksheeraj Sai Vepuri, Basar Demir, Jason Bohrer, Emily Shen, Jianfa Chen, Nan Jiang, Ankit Jain, Harihar Subramanyam, Mannat Singh, Chirag Nagpal

September 24, 2026

July 29, 2026

REINFORCEMENT LEARNING

NLP

Reinforcement Learning for Code Optimization

Pierre Chambon, Kunhao Zheng, Juliette Decugis, BenoƮt Sagot, Gabriel Synnaeve

July 29, 2026

July 17, 2026

CONVERSATIONAL AI

REINFORCEMENT LEARNING

Learning to Reason by Analogy via Retrieval-Augmented Reinforcement Fine-Tuning

Zilin Xiao, Qi Ma, Jason Chen, Xintao Chen, Avinash Atreya, Hanjie Chen, Vicente Ordonez

July 17, 2026

June 05, 2026

CONVERSATIONAL AI

RANKING AND RECOMMENDATIONS

Superintelligent Retrieval Agent: The Next Frontier of Agentic Retrieval

Zeyu Yang, Qi Ma, Jason Chen, Anshumali Shrivastava

June 05, 2026

Help Us Pioneer The Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.