Using Llama 3.2 3B Instruct on Fireworks AI
Implementation guide · Llama 3.2 · AI at Meta
ServerlessOpen Weights
Fireworks AI exposes Llama 3.2 3B Instruct through model ID accounts/fireworks/models/llama-v3p2-3b-instruct. 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
accounts/fireworks/models/llama-v3p2-3b-instruct— see the documentation for request format. - 3
Code Examples
Install
pip install openaiAPI key
FIREWORKS_API_KEYModel ID
accounts/fireworks/models/llama-v3p2-3b-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-v3p2-3b-instruct",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.10 |
| Output tokens | $0.10 |
Capabilities
Structured Outputs
About Llama 3.2 3B Instruct
Llama 3.2 3B Instruct is Meta's Llama 3.2 model. It offers a 128K-token context window with weights openly available for self-hosting and scores 34.7 on MMLU PRO.
Model Specs
Released2024-09-25
Parameters3.21B
Context128k
ArchitectureDecoder Only
Knowledge cutoff2023-12