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capacity

Discover Azure OpenAI model capacity and recommend optimal deployment locations.

Updated Apr 9, 2026
Search Tags:#Azure OpenAI#model availability#capacity discovery#quota analysis#deployment optimization
One-click install
npx skills add https://github.com/paidethon/Daily --skill capacity-paidethon
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: capacity
Source: https://github.com/paidethon/Daily/tree/main/.agents/skills/microsoft-foundry/models/deploy-model/capacity
Command: npx skills add https://github.com/paidethon/Daily --skill capacity-paidethon

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires az, and includes scripts (resource) components.

What problem does it solve?

This Skill helps you discover available Azure OpenAI model capacity across regions and projects, analyze quota limits, compare availability, and recommend optimal deployment locations based on capacity requirements.

Core Features & Use Cases

  • Capacity Discovery: Finds available Azure OpenAI model capacity across all accessible regions and projects.
  • Quota Analysis: Analyzes quota limits and compares availability.
  • Optimal Deployment: Recommends the best deployment location based on capacity requirements.
  • Use Case: If you need to deploy a model with sufficient capacity, this Skill can identify the most suitable region and project for your deployment.

Quick Start

Run the discover_and_rank script to find the best deployment location for your model. Example: ./scripts/discover_and_rank.sh -ModelName <model-name> -ModelVersion <version> -MinCapacity <target>

Frequently Asked Questions about capacity

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find Azure OpenAI model capacity across multiple regions?▼

You can discover Azure OpenAI model capacity by running the discover_and_rank script, which queries Azure REST APIs to find available TPM limits and deployment options across all accessible regions and projects.

What's the best way to analyze Azure OpenAI quota limits for optimal deployment locations?▼

The best way to analyze Azure OpenAI quota limits is using a capacity discovery tool that compares regional availability, ranks projects by TPM limits, and recommends the optimal deployment location based on your specific capacity requirements.

Do I need Azure CLI to discover Azure OpenAI model availability?▼

Yes, you need Azure CLI installed for authentication. The capacity discovery process uses Azure CLI to authenticate and then makes REST API calls to retrieve model availability and quota data across regions.

Can I check Azure OpenAI TPM availability before deploying a specific model version?▼

Yes, you can check TPM availability by running the discover_and_rank script with parameters for model name, version, and minimum capacity target to identify which regions can support your deployment needs.

What are the limitations of discovering Azure OpenAI capacity across regions?▼

Capacity discovery is limited to regions and projects you can access with your Azure credentials. It relies on Azure REST API data, so any regional restrictions or quota limitations in your subscription will directly affect the available results.

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