Azure OpenAI Models Token Limits

This Azure OpenAI blog post will explore the token limitations of AI models offered by Azure.

A critical factor to consider when developing and working with LLM apps and solutions is token limits.

Token limit is , how much text Azure’s models, including the well-known ChatGPT, can process per request or per day. This blog post aims to demystify token limits, highlighting their importance and providing strategies to manage them efficiently.

Understanding Token Limits

Token limits define the maximum number of tokens—parts of words or entire words—that can be processed in a single request or over a specified period. These limits are crucial for maintaining system performance and managing costs, as Azure OpenAI services are typically priced based on token usage.

Why are Token Limits Important?

Token limits play a significant role in:

  • Scalability: Ensuring that no single user or process can monopolize system resources, allowing the service to support multiple users effectively.
  • Cost Management: Helping users forecast and control expenses associated with using Azure’s AI services.
  • Efficiency: Promoting faster, more reliable AI responses by preventing overloads.

Token Limits for Azure OpenAI Models

Here’s a look at the typical token limits for various models provided by Azure OpenAI, which can help in planning and optimizing usage:

  • ChatGPT – 4,096 tokens per message list
  • GPT3.5 – 4,096 tokens per message list
  • GPT4 – 8,192 tokens per message list
  • GPT4-32K – 32,768 tokens per message list

Strategies for Managing Token Limits

To maximize the efficiency of Azure OpenAI services within these token limits, consider the following strategies:

  1. Optimize Input Data: Trim and condense data before sending it to the model to reduce token count and enhance response efficiency.
  2. Batch Requests: For large data sets, split the data into smaller chunks that fit within single-request token limits.
  3. Usage Monitoring: Regularly track token consumption through Azure’s monitoring tools to adjust usage patterns and stay within budget limits.
  4. Understand Pricing Structures: Knowing how costs correlate with token usage helps in budget planning and can prevent unexpected expenses.


Token limits are an essential aspect of using Azure OpenAI services efficiently. By understanding and managing these limits, developers and businesses can ensure smooth operation, effective cost management, and optimal use of AI capabilities.

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