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Model card on Hugging Face
Llama 4 Scout
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
- Context window
- 1M tokens
- Sizes
- 109B
- Licence
- llama4
Run Llama 4 Scout
Install it on a Pendra worker, then call it through the OpenAI-compatible API with a pdr_sk_ key.
Chat
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)Vision
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)Run Llama 4 Scout on your own UK infrastructure
Deploy a worker, install Llama 4 Scout, and start serving it through one sovereign API endpoint.