Last refreshed 2026-07-09. Next refresh: weekly.
Why use CodeLlama 34B Python on Fireworks AI?
Fireworks AI offers CodeLlama 34B Python with pay-as-you-go pricing at $0.90/1M input tokens. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.
Compare CodeLlama 34B Python across 4 providers to find the best fit for your use caseSetup 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-34b-pythonRequest 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-34b-python",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "accounts/fireworks/models/code-llama-34b-python", not the LLMReference slug "codellama-34b-python".
- 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.
Compare CodeLlama 34B Python Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Together AI | $0.80 | $0.80 |
| Fireworks AI | $0.90 | $0.90 |
| Microsoft Foundry | $1.54 | $1.77 |
| Replicate API | $0.20 | $1.00 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.90 |
| Output tokens | $0.90 |
Capabilities
About CodeLlama 34B Python
CodeLlama 34B Python is a specialized code generation model released by Meta on August 24, 2023. With 34 billion parameters, it excels in Python-specific tasks like code completion, infilling, and instruction following. This model offers AI engineers a powerful tool for enhancing coding workflows and productivity. Its architecture is optimized for understanding and generating complex code structures, making it particularly useful for software development tasks. The model is available in the Hugging Face Transformers format, facilitating easy integration into existing projects .