9 min read • September 2026
Enterprise Sizing Framework
How to Estimate AI Infrastructure Costs for SaaS Applications
By TokenMath Editorial & Engineering Team · Reviewed · Methodology
Most startup AI budgets fail because they multiply average prompt tokens by active users and stop there. Real-world bills are driven by peak concurrency overprovisioning, failure retries, compounding agent turns, and vector database IOPS.
1. The 5 Variables Every AI Budget Must Include
1. User Activity Volume (DAU × Requests/User)
Total monthly interactions = Daily Active Users × Average queries per day × 30.
2. Token Asymmetry Ratio (Input vs Output)
Separate input tokens (system + RAG + history) from output tokens (model response + reasoning chain).
3. Prompt Cache Hit Percentage (0% to 90%)
Estimate how much of your input context is static and reused across sessions.
4. Retry & Guardrail Penalty Buffer (10% to 25%)
Factor in schema parsing retries, moderation guardrails, and timeouts.
5. Vector Storage & Neural Reranker TCO
Include vector DB monthly namespace charges and reranking fees (e.g. Cohere Rerank $1.00/1k).
2. The Complete Monthly Forecasting Formula
Total Monthly Spend =
Monthly Queries × [ (Uncached Input × Input Rate) + (Cached Input × Cache Rate) + (Output × Output Rate) ] × (1 + Retry Rate) + Auxiliary Costs (Embeddings + Vector DB + Tools)
Simulate Your SaaS Unit Economics
Use the Monthly AI Cost Calculator for customer margin planning.