Using Llama 3.1 70B Instruct on Featherless
Implementation guide · Llama 3.1 · AI at Meta
Featherless exposes Llama 3.1 70B Instruct through model ID meta-llama/Meta-Llama-3.1-70B-Instruct. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-09-24. Next refresh: weekly.
Quick Start
- 1
- 2Use the Featherless SDK or REST API to call
meta-llama/Meta-Llama-3.1-70B-Instruct— see the documentation for request format. - 3
Code Examples
pip install openaiFEATHERLESS_API_KEYmeta-llama/Meta-Llama-3.1-70B-InstructUse exact Featherless catalog id in modelProvider.providerModelId (HF-style org/name). Not interchangeable with LLM Reference slugs.
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.featherless.ai/v1",
api_key=os.environ["FEATHERLESS_API_KEY"],
)
response = client.chat.completions.create(
model="meta-llama/Meta-Llama-3.1-70B-Instruct",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)Pricing on Featherless
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.72 |
| Output tokens | $0.72 |
Capabilities
About Llama 3.1 70B Instruct
The Llama 3.1 70B Instruct model is a cutting-edge large language model with 70 billion parameters, designed for instruction-following tasks. It features multilingual capabilities, supporting languages like English, German, French, and others. Fine-tuned using supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF), it excels in understanding and responding to user instructions. The model can handle a context length of up to 128k tokens, making it suitable for complex dialogue systems and applications requiring detailed responses.
Model Specs
Also available on(13)
Provider