Using Llama 4 Maverick 17B Instruct FP8 on Fireworks AI
Implementation guide · Llama 4 · AI at Meta
ServerlessOpen Weights
Fireworks AI exposes Llama 4 Maverick 17B Instruct FP8 through model ID llama-4-maverick-17b-128e-instruct-fp8. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-07-09. Next refresh: weekly.
Quick Start
- 1
- 2Use the Fireworks AI SDK or REST API to call
llama-4-maverick-17b-128e-instruct-fp8— see the documentation for request format.
Code Examples
Install
pip install openaiAPI key
FIREWORKS_API_KEYModel ID
llama-4-maverick-17b-128e-instruct-fp8Fireworks 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="llama-4-maverick-17b-128e-instruct-fp8",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks AI
Capabilities
VisionMultimodalStructured Outputs
About Llama 4 Maverick 17B Instruct FP8
Meta's Llama 4 Maverick 17B with 128 experts, FP8-optimized for cost-efficient inference. Supports native Model Router integration on Microsoft Foundry.
Model Specs
Released2025-04-05
Parameters400B (17B active)
Context1m
ArchitectureMixture of Experts
Knowledge cutoff2024-08