Azure OpenAI exposes davinci through model ID davinci. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-09-29. Next refresh: weekly.
Quick Start
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Code Examples
pip install openaiAZURE_OPENAI_API_KEYdavincidavinci is your Azure deployment name, not the underlying model name. Deployment names are set when you deploy a model in Azure AI Foundry / Azure OpenAI Studio.
import os
from openai import AzureOpenAI
client = AzureOpenAI(
azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"], # e.g. https://{resource}.openai.azure.com
api_key=os.environ["AZURE_OPENAI_API_KEY"],
api_version="2024-02-01"
)
response = client.chat.completions.create(
model="davinci", # your deployment name
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Azure OpenAI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $2.00 |
| Output tokens | $2.00 |
Capabilities
No model capability flags are currently sourced.
About davinci
Davinci, a sophisticated model within OpenAI's GPT-3 family, is renowned for its ability to handle complex tasks with exceptional proficiency 46. It excels in understanding nuanced language, solving logical puzzles, and generating creative content, making it highly effective for tasks like explaining character motives and performing detailed summarizations 47. While it is more costly and computationally intensive than models like Curie or Ada, its superior performance in interpreting complex language tasks justifies these demands 1.