Llama Guard 4 is a 12-billion-parameter safety classification model that detects harmful content in both model inputs and outputs. It is built by pruning the Llama 4 Scout foundation, keeping only the shared expert to give it a dense feedforward early-fusion architecture rather than a mixture-of-experts design, which lets it run on a single GPU with 24GB of VRAM. The model classifies content against the hazard categories defined in the MLCommons taxonomy along with code interpreter abuse, covering areas such as violent crimes, sexual content, hate speech, self-harm, and intellectual property. It evaluates multilingual text and can process mixed text-and-image prompts, combining the capabilities of the earlier Llama Guard 3-8B and 3-11B-vision models into a single classifier with added multi-image support. Meta reports that, compared to Llama Guard 3, version 4 improves English recall by about 4% and F1 by about 8%, with roughly 17 to 20% gains on multi-image detection. It is designed to safeguard multimodal Llama 4 applications while staying light enough for real-time prompt and response filtering.
Llama Guard 4 12B runs on 1 route through the qynio gateway. Compare residency, zero retention, and training posture at a glance — full data-handling detail per route below.
| Provider | Region | Zero data retention | Training | Input | Output |
|---|---|---|---|---|---|
| US | Zero data retention | No | $0.18 | $0.18 |
Llama Guard 4 12B runs on a single route through the qynio gateway today, so its availability is that provider's availability.
Name a second model in the same request and the gateway tries it on retriable errors, so a busy hour never has to reach your users. .
Measured over the last 30 days from each provider's official status feed via StatusGator. Refreshed hourly. See uptime for every provider qynio monitors.
Each route hosting Llama Guard 4 12B has its own privacy posture, residency, and no-KYC terms. Postures are maintained by qynio with a last-verification timestamp.
Zero data retention is on by default on Pay-as-you-go — no action required. No training on customer data. US; unknown; deposit available.
Call Llama Guard 4 12B through the qynio gateway with one API key. Let your coding agent set it up, or call it directly — qynio is drop-in compatible with the OpenAI, Anthropic, and Google AI SDKs.
Copy this and paste it into a coding agent like Claude Code, Cursor or Codex and it'll wire up qynio for you.
import OpenAI from "openai";const client = new OpenAI({apiKey: process.env.QYN_API_KEY,baseURL: "https://api.qyn.io/v3/compat",});const completion = await client.chat.completions.create({model: "deepinfra/meta-llama/Llama-Guard-4-12B",messages: [{ role: "user", content: "Hello" }],});console.log(completion.choices[0].message.content);
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