Estimate Azure AI Services costs for OpenAI (GPT-4o/4/3.5), Vision, Language, Speech, and Document Intelligence.
Last verified: May 2026
The estimator computes monthly cost across each Azure AI service: OpenAI (input tokens × $/1M + output tokens × $/1M, with model-specific rates), Document Intelligence (pages × per-page rate by model: prebuilt vs custom), Speech-to-Text (audio hours × per-hour rate by tier), Computer Vision (transactions × per-1K rate). Free tier allowances are subtracted from each before pricing.
The Azure AI Services Cost Estimator helps you project monthly costs for Azure's cognitive services including Azure OpenAI (GPT-4o, GPT-4, GPT-3.5), Computer Vision, Language Understanding, Speech Services, and Document Intelligence (Form Recognizer). Each service has unique pricing dimensions like tokens, transactions, pages, or audio hours. This tool consolidates pricing models into a single calculator for accurate budgeting.
Your team is building a customer support chatbot expected to handle 50,000 conversations/month, each averaging 2K input tokens + 500 output tokens. With GPT-4 Turbo: $1,750/month. The estimator suggests testing GPT-4o-mini for the same workload: $80/month. After A/B testing, GPT-4o-mini handles 95% of conversations with comparable quality — only complex escalations are routed to GPT-4. Total monthly: ~$160 — a 91% cost reduction.
Provisioned Throughput Units (PTUs) for Azure OpenAI are sold in monthly or yearly commitments and provide guaranteed capacity at predictable cost. The break-even vs. pay-per-token is typically around 100M tokens/month — below that, PAYG is cheaper. Above, PTUs eliminate rate limit issues AND save money.
GPT-4o is significantly cheaper than GPT-4 (roughly 50% less) AND faster, with comparable quality for most enterprise use cases. Many teams default to GPT-4 because that's what was available when they started — running a benchmark on GPT-4o is often the single highest-ROI optimization for an LLM-heavy app.
Embeddings (text-embedding-3-small/large) cost a fraction of completion tokens but rate-limit separately. For RAG architectures, your embedding cost is usually <5% of total spend even at scale. Don't optimize embedding usage at the expense of retrieval quality — completion costs dominate.
Azure OpenAI charges per 1,000 tokens separately for input (prompt) and output (completion) tokens. Pricing varies by model: GPT-4o is less expensive than GPT-4, and GPT-3.5-Turbo is the most economical. Provisioned Throughput Units (PTUs) offer predictable pricing for high-volume production workloads.
The free tier provides limited monthly transactions for evaluation purposes with lower rate limits. The standard tier offers pay-as-you-go pricing with higher rate limits and SLA guarantees. For production workloads, always use the standard tier.
Azure AI Services do not have built-in spending caps, but you can use Azure Cost Management budgets with alerts to monitor spending and set up action groups to notify or take automated action when costs exceed thresholds.
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