meta-llama/llama-guard-4-12b
Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM...
A dedicated public landing page for this synced catalog row.
Synced from the active catalog
Validated for gateway requests
Charged from your UAI balance
Same API key and billing flow
This page exists for direct linking, onboarding, and SEO. The same model row powers /v1/models, the public catalog, the app pricing screen, and request validation for /v1/chat/completions.
The same model route, but with one account, one balance, and one API shape.
Meta: Llama Guard 4 12B exposes 164K tokens, which makes it a good fit for large documents, transcripts, and retrieval-heavy chat flows.
The synced capabilities for this row indicate image or vision support, so you can route multimodal requests through the same UAI account and billing flow.
Call meta-llama/llama-guard-4-12b with the same UAI API key, the same /v1/chat/completions shape, and the same request validation used across the rest of the catalog.
Current synced numbers for this exact model row.
Need another option? Browse the full models catalog or compare rows in the signed-in pricing table.
Use this model with your UAI key over the standard OpenAI-compatible route.
Create a key in API Keys, then send requests to https://uai.sh/v1/chat/completions.
curl https://uai.sh/v1/chat/completions \
-H "Authorization: Bearer uai-YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "meta-llama/llama-guard-4-12b",
"messages": [{"role": "user", "content": "Say hi in one short sentence."}],
"stream": false
}'
from openai import OpenAI
client = OpenAI(base_url="https://uai.sh/v1", api_key="uai-YOUR_API_KEY")
response = client.chat.completions.create(
model="meta-llama/llama-guard-4-12b",
messages=[{"role": "user", "content": "Say hi in one short sentence."}],
stream=False
)
print(response.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://uai.sh/v1",
apiKey: "uai-YOUR_API_KEY"
});
const response = await client.chat.completions.create({
model: "meta-llama/llama-guard-4-12b",
messages: [{ role: "user", content: "Say hi in one short sentence." }],
stream: false
});
console.log(response.choices[0].message.content);
Other active rows to compare without leaving the public catalog.