--- description: Llama Guard 3 is a Llama-3.1-8B pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM inputs (prompt classification) and in LLM responses (response classification). It acts as an LLM – it generates text in its output that indicates whether a given prompt or response is safe or unsafe, and if unsafe, it also lists the content categories violated. title: llama-guard-3-8b image: https://developers.cloudflare.com/og-docs.png --- [Skip to content](#main-content) > Documentation Index > Fetch the complete documentation index at: https://developers.cloudflare.com/llms.txt > Use this file to discover all available pages before exploring further. ![Meta logo](https://docs-durable-objects-instance-replaced-errors.previews.developers.cloudflare.com/_astro/meta.CTzB_ysm.svg) # llama-guard-3-8b Text Generation • Meta Copy as Markdown|[View as Markdown](https://docs-durable-objects-instance-replaced-errors.previews.developers.cloudflare.com/workers-ai/models/llama-guard-3-8b/index.md)|[Agent setup](https://docs-durable-objects-instance-replaced-errors.previews.developers.cloudflare.com/agent-setup/) `@cf/meta/llama-guard-3-8b` * Cloudflare-hosted * LoRA Llama Guard 3 is a Llama-3.1-8B pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM inputs (prompt classification) and in LLM responses (response classification). It acts as an LLM – it generates text in its output that indicates whether a given prompt or response is safe or unsafe, and if unsafe, it also lists the content categories violated. | Model Info | | | ------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------- | | Context Window[ ↗](https://docs-durable-objects-instance-replaced-errors.previews.developers.cloudflare.com/workers-ai/platform/glossary/) | 131,072 tokens | | LoRA | Yes | | Unit Pricing | $0.48 per M input tokens, $0.03 per M output tokens | ## Playground Try out this model with Workers AI LLM Playground. It does not require any setup or authentication and is an instant way to preview and test a model directly in the browser. [Launch the LLM Playground](https://playground.ai.cloudflare.com/?model=@cf/meta/llama-guard-3-8b) ## Usage ```ts export interface Env { AI: Ai; } export default { async fetch(request, env): Promise { const messages = [ { role: "system", content: "You are a friendly assistant" }, { role: "user", content: "What is the origin of the phrase Hello, World", }, ]; const stream = await env.AI.run("@cf/meta/llama-guard-3-8b", { messages, stream: true, }); return new Response(stream, { headers: { "content-type": "text/event-stream" }, }); }, } satisfies ExportedHandler; ``` ```ts export interface Env { AI: Ai; } export default { async fetch(request, env): Promise { const messages = [ { role: "system", content: "You are a friendly assistant" }, { role: "user", content: "What is the origin of the phrase Hello, World", }, ]; const response = await env.AI.run("@cf/meta/llama-guard-3-8b", { messages }); return Response.json(response); }, } satisfies ExportedHandler; ``` ```py import os import requests ACCOUNT_ID = "your-account-id" AUTH_TOKEN = os.environ.get("CLOUDFLARE_AUTH_TOKEN") prompt = "Tell me all about PEP-8" response = requests.post( f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/meta/llama-guard-3-8b", headers={"Authorization": f"Bearer {AUTH_TOKEN}"}, json={ "messages": [ {"role": "system", "content": "You are a friendly assistant"}, {"role": "user", "content": prompt} ] } ) result = response.json() print(result) ``` ```sh curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/meta/llama-guard-3-8b \ -X POST \ -H "Authorization: Bearer $CLOUDFLARE_AUTH_TOKEN" \ -d '{ "messages": [{ "role": "system", "content": "You are a friendly assistant" }, { "role": "user", "content": "Why is pizza so good" }]}' ``` OpenAI compatible endpoints Workers AI also supports OpenAI compatible API endpoints for `/v1/chat/completions` and `/v1/embeddings`. For more details, refer to [Configurations](https://docs-durable-objects-instance-replaced-errors.previews.developers.cloudflare.com/workers-ai/configuration/open-ai-compatibility/). ## Parameters ▶messages\[\] `array`requiredAn array of message objects representing the conversation history. max\_tokens `integer`default: 256The maximum number of tokens to generate in the response. temperature `number`default: 0.6minimum: 0maximum: 5Controls the randomness of the output; higher values produce more random results. ▶response\_format{} `object`Dictate the output format of the generated response. ▶response `one of` ▶usage{} `object`Usage statistics for the inference request ## API Schemas (Raw) Input Output Was this helpful? YesNo ## On this page [![](https://docs-durable-objects-instance-replaced-errors.previews.developers.cloudflare.com/_astro/logo.te5VL_aD.svg)Docs](https://docs-durable-objects-instance-replaced-errors.previews.developers.cloudflare.com/) ```json {"@context":"https://schema.org","@type":"TechArticle","@id":"https://developers.cloudflare.com/workers-ai/models/llama-guard-3-8b/#page","headline":"llama-guard-3-8b (Meta) · Cloudflare AI docs · Cloudflare Workers AI docs","description":"Llama Guard 3 is a Llama-3.1-8B pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM inputs (prompt classification) and in LLM responses (response classification). 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