Using CodeLlama 34B on Fireworks AI
Implementation guide · Code Llama · AI at Meta
Fireworks AI exposes CodeLlama 34B through model ID accounts/fireworks/models/code-llama-34b. 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/code-llama-34b— see the documentation for request format. - 3
Code Examples
pip install openaiFIREWORKS_API_KEYaccounts/fireworks/models/code-llama-34bFireworks 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/code-llama-34b",
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
About CodeLlama 34B
CodeLlama 34B is a powerful generative text model developed by Meta, specifically tailored for code synthesis and understanding. With 34 billion parameters, it excels in code completion, infilling, and instruction following, particularly for Python programming. The model utilizes an auto-regressive transformer architecture and has been trained on a diverse dataset of programming languages, making it versatile for various coding tasks. Designed for both commercial and research applications, CodeLlama 34B offers AI engineers a robust tool for integrating advanced code generation capabilities into their projects. More details can be found on the model's Hugging Face page .