Llama 4 Scout

Name: Llama 4 Scout
Author: Meta

by Meta Chat · Vision · Tools

Llama 4 Scout is Meta's natively-multimodal mixture-of-experts model, activating 17B parameters per token from a larger expert pool for efficient inference. It reads images as well as text and supports an exceptionally long, million-token context, aimed at long-document and multimodal workloads.

Publisher: Meta (opens in a new tab)
API model name: llama4-scout:17b
Context window: 1M tokens
Sizes: 109B
Licence: llama4

Run Llama 4 Scout

Install it on a Pendra worker, then call it through our SDK with your pdr_sk_ API key.

Read the quickstart

from pendra import Pendra

client = Pendra(api_key="pdr_sk_...")

response = client.chat.completions.create(
    model="llama4-scout:17b",
    messages=[{"role": "user", "content": "Hello!"}],
)

print(response.choices[0].message.content)

import { Pendra } from "pendra";

const client = new Pendra({ apiKey: "pdr_sk_..." });

const response = await client.chat.completions.create({
  model: "llama4-scout:17b",
  messages: [{ role: "user", content: "Hello!" }],
});

console.log(response.choices[0].message.content);

from pendra import Pendra

client = Pendra(api_key="pdr_sk_...")

response = client.chat.completions.create(
    model="llama4-scout:17b",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What's in this image?"},
                {"type": "image_url", "image_url": {"url": "https://example.com/photo.jpg"}},
            ],
        }
    ],
)

print(response.choices[0].message.content)

import { Pendra } from "pendra";

const client = new Pendra({ apiKey: "pdr_sk_..." });

const response = await client.chat.completions.create({
  model: "llama4-scout:17b",
  messages: [
    {
      role: "user",
      content: [
        { type: "text", text: "What's in this image?" },
        { type: "image_url", image_url: { url: "https://example.com/photo.jpg" } },
      ],
    },
  ],
});

console.log(response.choices[0].message.content);

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Run Llama 4 Scout on infrastructure you trust.

Deploy a worker, install Llama 4 Scout, and start serving it through one private API.

Try it free Read the quickstart