Using CodeLlama 7B Instruct on Fireworks AI
Implementation guide · Code Llama · AI at Meta
Fireworks AI exposes CodeLlama 7B Instruct through model ID accounts/fireworks/models/code-llama-7b-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-7b-instruct— see the documentation for request format. - 3
Code Examples
pip install openaiFIREWORKS_API_KEYaccounts/fireworks/models/code-llama-7b-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-7b-instruct",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
No model capability flags are currently sourced.
About CodeLlama 7B Instruct
CodeLlama 7B Instruct is a specialized variant of Meta's CodeLlama family, designed for code synthesis and understanding tasks. With 7 billion parameters, it excels in code completion, infilling, and following instructions, particularly in Python programming. The model has been fine-tuned to generate code based on user prompts, ensuring safer and more reliable outputs. It's part of a broader collection ranging from 7B to 34B parameters, trained on a diverse dataset for handling various coding tasks effectively. AI engineers can leverage this model to integrate advanced code generation capabilities into their applications, enhancing productivity in software development.