Using Llama 3.1 8B Instruct on Featherless
Implementation guide · Llama 3.1 · AI at Meta
Featherless exposes Llama 3.1 8B Instruct through model ID meta-llama/Meta-Llama-3.1-8B-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-3.1-8B-Instruct— see the documentation for request format. - 3
Code Examples
pip install openaiFEATHERLESS_API_KEYmeta-llama/Meta-Llama-3.1-8B-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-3.1-8B-Instruct",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)Pricing on Featherless
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.05 |
| Output tokens | $0.08 |
Capabilities
About Llama 3.1 8B Instruct
The Llama 3.1 8B Instruct model, released on July 23, 2024, is a multilingual large language model with 8 billion parameters, optimized for instruction-following tasks. It features an enhanced transformer architecture, supporting languages like English, German, French, and others. The model excels in dialogue applications, having been fine-tuned using supervised fine-tuning and reinforcement learning with human feedback. Trained on approximately 15 trillion tokens with a December 2023 data cutoff, it outperforms many existing open-source and closed chat models in various benchmarks.
Model Specs
Provider