Using GPT-3.5 Turbo on Azure OpenAI

Implementation guide · GPT-3.5 · OpenAI

Serverless

Azure OpenAI exposes GPT-3.5 Turbo through model ID gpt-3.5-turbo. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-05-10. Next refresh: weekly.

Quick Start

  1. 1
    Create an account at Azure OpenAI and generate an API key.
  2. 2
    Use the Azure OpenAI SDK or REST API to call gpt-3.5-turbo — see the documentation for request format.
  3. 3
    You'll be billed $0.50/1M input, $1.50/1M output tokens. See full pricing.

Code Examples

Install
pip install openai
API key
AZURE_OPENAI_API_KEY
Model ID
gpt-3.5-turbo

gpt-3.5-turbo 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="gpt-3.5-turbo",  # your deployment name
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Pricing on Azure OpenAI

TypePrice (per 1M)
Input tokens$0.50
Output tokens$1.50

Capabilities

Structured Outputs

About GPT-3.5 Turbo

GPT-3.5 Turbo is an advanced language model developed by OpenAI, showcasing significant advancements over GPT-3 and GPT-3.5. As the engine behind the popular ChatGPT application, it excels in tasks like text generation, translation, question answering, summarization, and code generation. This model employs Reinforcement Learning from Human Feedback (RLHF) to enhance accuracy and produce policy-optimized responses. Despite its prowess, it has a knowledge cutoff of September 2021 and can demonstrate biases from its training data. Occasionally, it may generate incorrect or nonsensical content, known as "hallucination," and is sensitive to input phrasing variations.

Model Specs

Released2023-03-01
Parameters20B
Context16k
ArchitectureDecoder Only
Knowledge cutoff2021-09

Provider

Azure OpenAI

Microsoft

Redmond, Washington, United States