Engineering & AI Economics

AI & Developer Calculators

Architect your infrastructure with confidence. Estimate LLM API token costs, compare AWS vs GCP pricing, and calculate your exact SaaS COGS.

AI & Generative Models

Cloud & Infrastructure

Database & Backend Scaling

SaaS & API Economics

DevOps & Project Estimation

Engineering Rules of Thumb

The Shift-Left Paradigm

A bug found in production costs 100x more to fix than a bug found during the design phase, and 15x more than during the coding phase. Invest in CI/CD.

API Egress Traps

Inbound data to cloud providers (AWS/GCP) is usually free. Outbound data (egress) is where bills explode. Always cache heavily at the Edge/CDN level.

The 1-Second Rule

For e-commerce and SaaS, a 1-second delay in page load time yields a 7% loss in conversions, 11% fewer page views, and a 16% decrease in customer satisfaction.

Pricing Accuracy & API Disclaimer

Cloud infrastructure and LLM API pricing (OpenAI, Anthropic, AWS) change rapidly. Our calculators use the latest publicly available tiered pricing, but actual billing may vary based on your Enterprise agreements, reserved instances, or geographical server regions. Always consult your vendor's official pricing page for final budget approvals.

Frequently Asked Questions

How do you estimate AI Token Costs vs. Words?
As a general rule of thumb for English text, 1 token is approximately 4 characters or 0.75 words. Therefore, 100 tokens roughly equal 75 words. Our AI Token Calculators automatically convert your expected word counts into token usage to accurately estimate API costs.
What is the difference between Serverless and Dedicated Server costs?
Dedicated servers (like AWS EC2) charge you a flat rate per hour regardless of traffic. Serverless functions (like AWS Lambda or Vercel Edge) charge you per invocation and compute duration. Serverless is incredibly cheap for low-traffic apps, but can become exponentially more expensive than dedicated servers at massive scale.
How do I calculate the cost of a RAG (Retrieval-Augmented Generation) application?
RAG apps have three distinct cost layers: 1) The Embedding API cost to convert user queries to vectors, 2) The Vector Database cost (e.g., Pinecone) to store and query the embeddings, and 3) The LLM API cost (e.g., GPT-4o) to generate the final response. You must calculate all three to find your true cost per query.