Understanding Azure OpenAI Service Quotas and Limits: A Beginner-Friendly Guide
Azure OpenAI Service allows developers, researchers, and students to integrate powerful AI models like GPT-4, GPT-3.5, and DALL·E into their applications. But with great power comes great responsibility and limits. Before you dive into building your next AI-powered solution, it's crucial to understand how quotas and limits work in the Azure OpenAI ecosystem. This guide is designed to help students and beginners easily understand the concept of quotas, limits, and how to manage them effectively. What Are Quotas and Limits? Think of Azure's quotas as your "AI data pack." It defines how much you can use the service. Meanwhile, limits are hard boundaries set by Azure to ensure fair use and system stability. Quota The maximum number of resources (e.g., tokens, requests) allocated to your Azure subscription. Limit The technical cap imposed by Azure on specific resources (e.g., number of files, deployments). Key Metrics: TPM & RPM Tokens Per Minute (TPM) TPM refers to how many tokens you can use per minute across all your requests in each region. A token is a chunk of text. For example, the word "Hello" is 1 token, but "Understanding" might be 2 tokens. Each model has its own default TPM. Example: GPT-4 might allow 240,000 tokens per minute. You can split this quota across multiple deployments. Requests Per Minute (RPM) RPM defines how many API requests you can make every minute. For instance, GPT-3.5-turbo might allow 350 RPM. DALL·E image generation models might allow 6 RPM. Deployment, File, and Training Limits Here are some standard limits imposed on your OpenAI resource: Resource Type Limit Standard model deployments 32 Fine-tuned model deployments 5 Training jobs 100 total per resource (1 active at a time) Fine-tuning files 50 files (total size: 1 GB) Max prompt tokens per request Varies by model (e.g., 4096 tokens for GPT-3.5) How to View and Manage Your Quota Step-by-Step: Go to the Azure Portal. Navigate to your Azure OpenAI resource. Click on "Usage + quotas" in the left-hand menu. You will see TPM, RPM, and current usage status. To Request More Quota: In the same "Usage + quotas" panel, click on "Request quota increase". Fill in the form: Select the region. Choose the model family (e.g., GPT-4, GPT-3.5). Enter the desired TPM and RPM values. Submit and wait for Azure to review and approve. What is Dynamic Quota? Sometimes, Azure gives you extra quota based on demand and availability. “Dynamic quota” is not guaranteed and may increase or decrease. Useful for short-term spikes but should not be relied on for production apps. Example: During weekends, your GPT-3.5 TPM may temporarily increase if there's less traffic in your region. Best Practices for Students Monitor Regularly: Use the Azure Portal to keep an eye on your usage. Batch Requests: Combine multiple tasks in one API call to save tokens. Start Small: Begin with GPT-3.5 before requesting GPT-4 access. Plan Ahead: If you're preparing a demo or a project, request quota in advance. Handle Limits Gracefully: Code should manage 429 Too Many Requests errors. Quick Resources Azure OpenAI Quotas and Limits How to Request Quota in Azure Join the Conversation on Azure AI Foundry Discussions! Have ideas, questions, or insights about AI? Don't keep them to yourself! Share your thoughts, engage with experts, and connect with a community that’s shaping the future of artificial intelligence. 🧠✨ 👉 Click here to join the discussion!
How to Optimize your Codespaces: Pro-tips for managing quotas
Now that GitHub Codespaces is free for anyone, you might be surprised to see how fast you can hit the free quota. Here are four things you can do to make the most out of the 90 hours you get every month (and 180 hours if you are a student).
Hard quotas not being enforced
Hello Win IT Pro! I've got a bit of an issue here. I'll try to explain my team's objective and what we've done. We're an R&D IT hosting organization. We want to set up network shares for our various projects to buy from us. But we need to limit the size of that network share. It was decided to setup multiple DFS servers (Server 2016) so we have redundancy if one fails. Next we created a series of folders, and using FSRM to set quotas. Then we give permission (via a Security Group) to that project's folder to the project admin; the project admin will have Full Control so they can create subfolders & manage permissions to their individual project share. The problem I've run into, that I can't seem to figure out, is that setting a quota on the project folder prevents that folder from exceeding the quota. However, if you make a folder within it (what I'm calling a "subfolder"), and then you'll be able to place files in excess of the quota. So to maybe illustrate it: Project Folder: 100GB quota > File 1: 90GB in size (does not exceed quota) >Subfolder>File 2: 110GB in size (exceeds quota of "Project Folder") I also tried setting up SMB shares, but the quotas are only sticking for as long as the user's current session lasts. That is, they can map the drive but upon rebooting their computer they can then exceed the quota limit (all are Windows 10). Also, upon restart, the user no longer sees the limit in Explorer "This PC" screen. I accept that maybe I'm going about this the wrong way. But I thought quotas would be the way to go & I can't seem to find anything on Google searches that helps me understand why this happening. When I read the Microsoft documentation it seems to indicate that a Hard Quota should prevent anything from exceeding this quota (100GB in this example). So what am I missing? Or is there a better way to go about this? Thanks a ton for your replies! Happy to provide additional info!
