Llama Guard 3 1B is the ultra-compact variant of Meta's safety classifier series, targeting deployments where inference latency and compute cost are critical constraints. With only 1 billion parameters it is designed to run inline — checking every prompt and response — without materially degrading end-to-end latency in high-throughput systems.
It shares the same hazard taxonomy alignment and structural output format as its 8B sibling, but trades some classification accuracy for dramatically lower resource usage. It is best suited as a fast first-pass filter in tiered moderation pipelines, escalating borderline cases to a larger classifier or human review.
Key Features
Sub-second classification latency even on modest CPU hardware
Shares MLCommons taxonomy categories with the larger Llama Guard models
Structured label output for easy integration with routing logic
Open weights enabling fully offline, air-gapped moderation
Low VRAM footprint allows co-deployment on the same GPU as a generation model
Supports both single-turn and multi-turn conversation inputs
Ideal Use Cases
Inline real-time moderation in high-traffic LLM APIs
Edge device content filtering for offline or embedded AI systems
First-pass triage in a multi-tier content safety pipeline
Lightweight pre-screening before invoking more expensive classifiers
IoT or mobile deployments requiring on-device policy enforcement
Example Prompts for Llama Guard 3 1B
Technical Specifications
| Provider | Meta |
| Category | Text |
| Modality | Text -> Text |
Frequently Asked Questions
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