Using CodeLlama 34B Instruct on Fireworks AI
Implementation guide · Code Llama · AI at Meta
Fireworks AI exposes CodeLlama 34B Instruct through model ID accounts/fireworks/models/code-llama-34b-instruct. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-09-18. Next refresh: weekly.
Quick Start
- 1
- 2Use the Fireworks AI SDK or REST API to call
accounts/fireworks/models/code-llama-34b-instruct— see the documentation for request format. - 3
Code Examples
pip install openaiFIREWORKS_API_KEYaccounts/fireworks/models/code-llama-34b-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/code-llama-34b-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
No model capability flags are currently sourced.
About CodeLlama 34B Instruct
CodeLlama 34B Instruct is a powerful generative text model developed by Meta, specifically designed for code synthesis and understanding tasks. With 34 billion parameters, it excels in code completion, infilling, and instruction following, making it ideal for AI engineers working on coding assistants and automated code generation tools. While supporting multiple languages, it has a particular focus on Python. Trained between January and July 2023 on a dataset similar to Llama 2, this model offers state-of-the-art performance for commercial and research applications in code-related tasks. For more details, visit the model's page on Hugging Face .