Llama Guard
Filter models that check chatbot requests and replies for dangerous topics against a list of categories. Version 4 also checks images. Russian is not officially supported.
- Developer
- Meta, USA
- First release
- Dec 2023
- Latest release
- Apr 2025
- Sizes
- 1B – 12B
- License
- Commercial use with conditionsLlama 2, 3.1 and 4 licenses: commercial use allowed with restrictions
- Russian
- Not supported
- Ready-made builds
- GGUF, AWQ
- Running
- Available in OllamaAlso runs without a GPU
- Industries
- Security, Customer support
What it does
- Checking user questions to the bot
- Checking bot replies before sending
- Reporting which rule category was violated
Where it is used
Hardware requirements
Versions
- Llama Guard 4 12B (текст и картинки)
- Llama Guard 3 1B и 11B Vision
- Llama Guard 3 8B
- Llama Guard 2 8B
- Llama Guard 7B
How to run it
I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems. Quantization compresses a model so it takes less video memory and runs on more modest hardware. Answers change slightly, so quality is checked on your own examples.
Frequently asked questions
Can Llama Guard be used in a commercial project?
With conditions. License: Llama 2, 3.1 and 4 licenses: commercial use allowed with restrictions. Restrictions vary — region, company revenue, attribution requirements. Have a lawyer check the terms before a commercial launch.
What hardware does Llama Guard need?
At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.
Does Llama Guard support Russian?
No. The model card lists its languages and Russian is not among them.
Where can I download Llama Guard and what does it cost?
The Llama Guard weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.
How I deploy it for clients
- SelectionI pick the model size for your task and hardware and test it on your examples.
- DeploymentI deploy it on your server or in a closed network and provide an API.
- Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
- IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.
Comparisons
Similar models
Safety filters for 119 languages, Russian among them. The Stream version checks a bot's reply while it is being generated and can cut it off on the fly.
DetailsModeration and safetyShieldGemmaGoogle · USACommercial use with conditionsGemma-based filters: they check text for dangerous and offensive content, and ShieldGemma 2 checks images. Focused on English.
DetailsModeration and safetyGranite GuardianIBM · USACommercial use allowedIBM judge models: they catch harm, profanity and jailbreak attempts, and in RAG and agents check whether an answer is grounded in the documents. You can state your own rule in words.
DetailsSource: huggingface.co/meta-llama/Llama-Guard-4-12B. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.


