As a user of ChatGPT API, it’s essential to understand the concept of rate limits and how they affect the performance of the API. In this article, we’ll explore rate limits, why they’re implemented, the rate limits for ChatGPT API, how they work, and what happens when you hit a rate limit error.
What are ChatGPT Rate Limits?
A rate limit is a safeguard that an API employs to limit the frequency with which a user or client can interact with the server during a specific time window.. It’s a way to prevent abuse or misuse of the API and ensure fair access to everyone.
How do ChatGPT Rate Limits API Performance?
The API’s performance can be affected if the rate limits are not set up correctly. A potential threat to the API is the possibility of a malicious actor launching a barrage of requests to overwhelm the system and create disruptions in service. This can cause performance issues and slow down the API for all users. By setting rate limits, ChatGPT can prevent this kind of activity and ensure that the API performs optimally.
What is the Reason for Implementing ChatGPT Rate Limits on APIs?
ChatGPT Rate limits are a standard practice implemented in APIs to serve several purposes.
- To protect against abuse or misuse of the API.
- With the goal of providing fair access to the API to all users.
- To help manage the aggregate load on the API’s infrastructure.
What are the Rate Limits for ChatGPT API?
At ChatGPT, rate limits are implemented at the organization level rather than the individual user level. The rate limit for accessing an endpoint depends on both the endpoint itself and the type of account you have. This limit is measured in two ways: RPM (requests per minute) and TPM (tokens per minute). This ensures that our services are available to all users and prevents excessive usage by any individual or group, which can lead to service degradation for others. The default rate limits for ChatGPT API are as follows:
| TYPE | 1 TPM EQUALS |
| davinci | 1 token per minute |
| curie | 25 tokens per minute |
| babbage | 100 tokens per minute |
| ada | 200 tokens per minute |
| Free trial users | Pay-as-you-go users (first 48 hours) | Pay-as-you-go users (after 48 hours) |
| Chat: 20 RPM | Chat: 60 RPM | Chat: 3,500 RPM |
| Codex: 150,000 TPM | Codex: 250,000 TPM | Codex: 350,000 TPM |
| Edit: 20 RPM | Edit: 60 RPM | Edit: 90,000 TPM |
| Image: 50 images/min | Image: 50 images/min | Image: 50 images/min |
| Audio: 50 RPM | Audio: 50 RPM | Audio: 50 RPM |
It’s worth noting that either option can trigger the rate limit, depending on which limit is reached first. For instance, if you send 20 requests to the Codex endpoint using only 100 tokens, you may hit the limit even if you haven’t consumed all 40k tokens within those 20 requests.
How do ChatGPT Rate Limits Work?
If you’re using an API that has a rate limit of 60 requests per minute and a token limit of 150k DaVinci tokens per minute, you’ll be constrained by whichever limit you reach first. This means that you may reach your limit in terms of the number of requests you can make per minute, or you may run out of tokens before you reach the request limit.
To put it into perspective, if your maximum requests per minute is 60, this equates to approximately 1 request per second. Therefore, it’s important to be mindful of both limits to ensure that your API usage remains within the acceptable limits and that your application runs smoothly. If you send 1 request every 800ms, once you hit your rate limit, you’d only need to make your program sleep 200ms to send one more request, or subsequent requests would fail.
At the default rate of 3,000 requests per minute, customers can efficiently transmit one request every 20 milliseconds, which is equivalent to one request every 0.02 seconds.”
This version is more concise, uses stronger verbs (“efficiently transmit” instead of “effectively send”), and eliminates the repetition of “every” for better readability.
How does encountering a rate limit error impact my system or application?
If a user hits a rate limit, it means they have made too many requests in a short period of time, and the API will refuse to fulfill further requests until a specified amount of time has passed. Rate limit errors will appear with a message indicating that the limit has been reached and the number of requests per minute or tokens per minute that were exceeded.
Rate limits vs max_tokens
Each model provided by OpenAI has a maximum number of tokens that can be passed in as input when making a request. The maximum number of tokens cannot be increased beyond the limit specified by OpenAI. For example, if a user is using text-ada-001, the maximum number of tokens they can send to the model is 2,048 tokens per request.
GPT-4 rate limits
As GPT-4 is rolled out, it will be equipped with more stringent rate limits to effectively cope with the anticipated demand. The default rate limits for GPT-4/GPT-4-0314 will be set at 40,000 TPM and 200 RPM, ensuring optimal performance and user satisfaction. Default rate limits for GPT-4-32k/GPT-4-32k-0314 are 80k RPM and 400 RPM. Users can contact OpenAI to request a rate limit increase or order dedicated capacity, but note that OpenAI may not be able to service all requests expediently.
In conclusion
rate limits are an essential component of OpenAI’s API infrastructure, helping to prevent abuse or misuse, ensure fair access for all users, and manage the aggregate load on their infrastructure. Users should be aware of the rate limits for their specific account and endpoint, and contact OpenAI to request an increase in rate limits if needed. By following these guidelines, users can maximize their use of OpenAI’s API while maintaining the quality of service for all users.
