Meta Llama 4 Scout on W&B Inference
Price per 1M tokens
$0.17 (input)
$0.66 (output)
Parameters
70B
109B
Context window
64K
Release date
Apr 2024
Meta Llama 4 Scout inference details
Llama 4 Scout integrates text and image understanding, making it suitable for multimodal applications such as visual Q&A, content moderation, captioning, and analysis tasks involving images combined with textual data. It efficiently balances computational load via a mixture-of-experts architecture.
Created by: Meta
License: other
🤗 model card: Llama-4-Scout-17B-16E-Instruct
import openai
import weave
# Weave autopatches OpenAI to log LLM calls to W&B
weave.init("<team>/<project>")
client = openai.OpenAI(
# The custom base URL points to W&B Inference
base_url='https://api.inference.wandb.ai/v1',
# Get your API key from https://wandb.ai/authorize
# Consider setting it in the environment as OPENAI_API_KEY instead for safety
api_key="<your-apikey>",
# Team and project are required for usage tracking
project="<team>/<project>",
)
response = client.chat.completions.create(
model="meta-llama/Llama-4-Scout-17B-16E-Instruct",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Tell me a joke."}
],
)
print(response.choices[0].message.content)
Meta Llama 4 resources
A primer on building successful AI agents
W&B Inference powered by CoreWeave guide
