Capacity Planning Guide
Comprehensive guide for planning Microsoft Foundry capacity, including cost analysis, model selection, and workload calculations.
Table of Contents: Cost Comparison: TPM vs PTU · Production Workload Examples · Model Selection and Deployment Type Guidance
Cost Comparison: TPM vs PTU
Official Pricing Sources:
- Azure OpenAI Service Pricing - Official pay-per-token rates
- PTU Costs and Billing Guide - PTU hourly rates and capacity planning
TPM (Standard) Pricing:
- Pay-per-token for input/output
- No upfront commitment
- Rates: See Azure OpenAI Pricing
- GPT-4o: ~$0.0025-$0.01/1K tokens
- GPT-4 Turbo: ~$0.01-$0.03/1K
- GPT-3.5 Turbo: ~$0.0005-$0.0015/1K
- Best for: Variable workloads, unpredictable traffic
PTU (Provisioned) Pricing:
- Hourly billing:
$/PTU/hr × PTUs × 730 hrs/month - Monthly commitment with Reservations discounts
- Rates: See PTU Billing Guide
- Use PTU calculator to determine requirements (Microsoft Foundry → Operate → Quota → Provisioned Throughput Unit tab)
- Best for: High-volume (>1M tokens/day), predictable traffic, guaranteed throughput
Cost Decision Framework (Analytical Guidance):
Step 1: Calculate monthly TPM cost
Monthly TPM cost = (Daily tokens × 30 days × $price per 1K tokens) / 1000
Step 2: Calculate monthly PTU cost
Monthly PTU cost = Required PTUs × 730 hours/month × $PTU-hour rate
(Get Required PTUs from Microsoft Foundry portal: Microsoft Foundry → Operate → Quota → Provisioned Throughput Unit tab)
Step 3: Compare
Use PTU when: Monthly PTU cost < (Monthly TPM cost × 0.7)
(Use 70% threshold to account for commitment risk)Example Calculation (Analytical):
Scenario: 1M requests/day, average 1,000 tokens per request
- Daily tokens: 1,000,000 × 1,000 = 1B tokens/day
- TPM Cost (using GPT-4o at $0.005/1K avg): (1B × 30 × $0.005) / 1000 = ~$150,000/month
- PTU Cost (estimated 100 PTU at ~$5/PTU-hour): 100 PTU × 730 hours × $5 = ~$365,000/month
- Decision: Use TPM (significantly lower cost for this workload)
Important: Always use the official Azure Pricing Calculator and Microsoft Foundry portal PTU calculator (Microsoft Foundry → Operate → Quota → Provisioned Throughput Unit tab) for exact pricing by model, region, and workload. Prices vary by region and are subject to change.
Production Workload Examples
To estimate quota requirements, use real-world production scenarios with capacity calculations for gpt-4, version 0613 (from Azure Foundry Portal calculator):
| Workload Type | Calls/Min | Prompt Tokens | Response Tokens | Cache Hit % | Total Tokens/Min | PTU Required | TPM Equivalent |
|---|---|---|---|---|---|---|---|
| RAG Chat | 10 | 3,500 | 300 | 20% | 38,000 | 100 | 38K TPM |
| Basic Chat | 10 | 500 | 100 | 20% | 6,000 | 100 | 6K TPM |
| Summarization | 10 | 5,000 | 300 | 20% | 53,000 | 100 | 53K TPM |
| Classification | 10 | 3,800 | 10 | 20% | 38,100 | 100 | 38K TPM |
How to Estimate Your Production Quota Requirements:
To calculate your quota needs for production deployments, follow these steps:
- Determine your peak calls per minute: Monitor or estimate maximum concurrent requests
- Measure token usage: Average prompt size + response size
- Account for cache hits: Prompt caching can reduce effective token count by 20-50%
- Calculate total tokens/min: (Calls/min × (Prompt tokens + Response tokens)) × (1 - Cache %)
- Choose deployment type:
- TPM (Standard): Allocate 1.5-2× your calculated tokens/min for headroom
- PTU (Provisioned): Use Microsoft Foundry portal PTU calculator for exact PTU count (Microsoft Foundry → Operate → Quota → Provisioned Throughput Unit tab)
Example Calculation (RAG Chat Production):
- Peak: 10 calls/min
- Prompt: 3,500 tokens (context + question)
- Response: 300 tokens (answer)
- Cache: 20% hit rate (reduces prompt tokens by 20%)
- Total TPM needed: (10 × (3,500 × 0.8 + 300)) = 31,000 TPM
- With 50% headroom: 46,500 TPM → Round to 50K TPM deployment
PTU Recommendation: For the combined workload (40 calls/min, 135K tokens/min total), use 200 PTU (from calculator above).
Model Selection and Deployment Type Guidance
Official Documentation:
- Choose the Right AI Model for Your Workload - Microsoft Architecture Center
- Azure OpenAI Models - Model capabilities, regions, and quotas
- Understanding Deployment Types - Standard vs Provisioned guidance
Model Characteristics (from official Azure OpenAI documentation):
| Model | Key Characteristics | Best For |
|---|---|---|
| GPT-4o | Matches GPT-4 Turbo performance in English text/coding, superior in non-English and vision tasks. Cheaper and faster than GPT-4 Turbo. | Multimodal tasks, cost-effective general purpose, high-volume production workloads |
| GPT-4 Turbo | Superior reasoning capabilities, larger context window (128K tokens) | Complex reasoning tasks, long-context analysis |
| GPT-3.5 Turbo | Most cost-effective, optimized for chat and completions, fast response time | Simple tasks, customer service, high-volume low-cost scenarios |
| GPT-4o mini | Fastest response time, low latency | Latency-sensitive applications requiring immediate responses |
| text-embedding-3-large | Purpose-built for vector embeddings | RAG applications, semantic search, document similarity |
Deployment Type Selection (from official deployment types guide):
| Traffic Pattern | Recommended Deployment Type | Reason |
|---|---|---|
| Variable, bursty traffic | Standard or Global Standard (pay-per-token) | No commitment, pay only for usage |
| Consistent high volume | Provisioned types (PTU) | Reserved capacity, predictable costs |
| Large batch jobs (non-time-sensitive) | Global Batch or DataZone Batch | 50% cost savings vs Standard |
| Low latency variance required | Provisioned types | Guaranteed throughput, no rate limits |
| No regional restrictions | Global Standard or Global Provisioned | Access to best available capacity |
Capacity Planning Approach (from PTU onboarding guide):
To calculate and estimate your capacity requirements:
- Calculate your TPM requirements: Determine required tokens per minute based on your expected workload
- Use the built-in capacity planner: Available in Microsoft Foundry portal (Microsoft Foundry → Operate → Quota → Provisioned Throughput Unit tab)
- Input your metrics: Enter input TPM and output TPM based on your workload characteristics
- Get PTU recommendation: The calculator provides PTU allocation recommendation
- Compare costs: Evaluate Standard (TPM) vs Provisioned (PTU) using the official pricing calculator
Note: Microsoft does not publish specific "X requests/day = Y TPM" recommendations as capacity requirements vary significantly based on prompt size, response length, cache hit rates, and model choice. Use the built-in capacity planner with your actual workload characteristics.