Using CodeLlama 34B on Fireworks AI

Implementation guide · Code Llama · AI at Meta

ProvisionedOpen Weights

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. 1
    Create an account at Fireworks AI and generate an API key.
  2. 2
    Use the Fireworks AI SDK or REST API to call accounts/fireworks/models/code-llama-34b — see the documentation for request format.
  3. 3
    You'll be billed $0.90/1M input, $0.90/1M output tokens. See full pricing.

Code Examples

Install
pip install openai
API key
FIREWORKS_API_KEY
Model ID
accounts/fireworks/models/code-llama-34b

Fireworks 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

TypePrice (per 1M)
Input tokens$0.90
Output tokens$0.90

Capabilities

Structured Outputs

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 .

Model Specs

Released2023-08-24
Parameters34B
Context100k
ArchitectureDecoder Only
Knowledge cutoff2024-03

Provider

Fireworks AI

San Mateo, California, United States