Using Llama Guard 2 8B on Fireworks AI
Implementation guide · Llama Guard · AI at Meta
Fireworks AI exposes Llama Guard 2 8B through model ID accounts/fireworks/models/llama-guard-2-8b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-09-18. Next refresh: weekly.
Quick Start
- 1
- 2Use the Fireworks AI SDK or REST API to call
accounts/fireworks/models/llama-guard-2-8b— see the documentation for request format. - 3
Code Examples
pip install openaiFIREWORKS_API_KEYaccounts/fireworks/models/llama-guard-2-8bFireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="accounts/fireworks/models/llama-guard-2-8b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
No model capability flags are currently sourced.
About Llama Guard 2 8B
Llama Guard 2 is an 8B-parameter LLM built on the Llama 3 architecture, specifically designed for content moderation tasks. Released by Meta on April 18, 2024, it excels in classifying both inputs and outputs of LLMs across 11 safety categories. The model generates text outputs indicating whether content is safe or unsafe, providing detailed feedback on violations. It aims to enhance user experience by minimizing false positives while maintaining high accuracy in content moderation, supporting developers in creating safer AI applications .