Last refreshed 2026-09-18. Next refresh: weekly.
Why use CodeLlama 13B Instruct on Fireworks AI?
Fireworks AI offers CodeLlama 13B Instruct with pay-as-you-go pricing at $0.20/1M input tokens. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.
Setup recipe
Python + curlpip install openaiexport FIREWORKS_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],accounts/fireworks/models/code-llama-13b-instructRequest example
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-13b-instruct",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "accounts/fireworks/models/code-llama-13b-instruct", not the LLMReference slug "codellama-13b-instruct".
- 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".
- The examples expect FIREWORKS_API_KEY; rename it only if your application config maps the new variable.
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
No model capability flags are currently sourced.
About CodeLlama 13B Instruct
CodeLlama 13B Instruct is a specialized generative text model developed by Meta, released on August 24, 2023. Part of the Code Llama family, this 13B parameter model is optimized for instruction-following and code-related tasks. It excels in code completion, infilling, and Python programming, utilizing an auto-regressive transformer architecture. Trained on a diverse dataset similar to Llama 2, it offers robust understanding of programming languages and practices. The model incorporates safety mechanisms to reduce harmful content generation, making it suitable for real-world applications. AI engineers can access and utilize this model through the Hugging Face platform .