Using Llama 3.3 70B Instruct on Fireworks AI
Implementation guide · Llama 3.3 · AI at Meta
ServerlessOpen Weights
Fireworks AI exposes Llama 3.3 70B Instruct through model ID accounts/fireworks/models/llama-v3p3-70b-instruct. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-10-17. Next refresh: weekly.
Quick Start
- 1
- 2Use the Fireworks AI SDK or REST API to call
accounts/fireworks/models/llama-v3p3-70b-instruct— see the documentation for request format. - 3
Code Examples
Install
pip install openaiAPI key
FIREWORKS_API_KEYModel ID
accounts/fireworks/models/llama-v3p3-70b-instructFireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="accounts/fireworks/models/llama-v3p3-70b-instruct",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.90 |
| Output tokens | $0.90 |
Capabilities
Structured Outputs
About Llama 3.3 70B Instruct
Llama 3.3 70B Instruct is Meta's text-only, instruction-tuned 70B Llama 3.3 model for multilingual assistant-style chat, with a 128K-token context window and openly downloadable weights.
Model Specs
Released2024-12-06
Parameters70B
Context128K
ArchitectureDecoder Only
Knowledge cutoff2023-12