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Using Llama 4 Scout 17B-16E Instruct on Together AI

Implementation guide · Llama 4 · AI at Meta

ServerlessOpen Source

Quick Start

  1. 1
    Create an account at Together AI and generate an API key.
  2. 2
    Use the Together AI SDK or REST API to call llama-4-scout-17b-16e-instruct — see the documentation for request format.

Code Examples

Install
pip install together
API key
TOGETHER_API_KEY
Model ID
llama-4-scout-17b-16e-instruct

Together uses "organization/model-name" format, e.g. "meta-llama/Llama-4-Scout-17B-16E-Instruct" or "Qwen/QwQ-32B". See the Together model catalog for the exact ID.

from together import Together

client = Together()  # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
    model="llama-4-scout-17b-16e-instruct",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

About Together AI

Platform for running open-source and proprietary LLMs

Together AI is a platform for running open-source and proprietary LLMs with fast serverless and dedicated endpoints at competitive inference pricing.

Pricing on Together AI

Capabilities

Structured Outputs

About Llama 4 Scout 17B-16E Instruct

Meta's Llama 4 Scout is a 17-billion parameter mixture-of-experts model with 16 expert routing. Optimized for efficient inference on edge and cloud environments with strong multi-turn conversation capabilities. Available on Cloudflare Workers AI.

Model Specs

Released2025-04-05
Parameters17B
Context328K
ArchitectureMixture of Experts
Knowledge cutoff2024-08

Provider

Together AI
Together AI

San Francisco, California, United States