Using Llama 4 Scout 17B-16E Instruct on Together AI
Implementation guide · Llama 4 · AI at Meta
ServerlessOpen Source
Quick Start
- 1
- 2Use 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 togetherAPI key
TOGETHER_API_KEYModel ID
llama-4-scout-17b-16e-instructTogether 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