Research

AI and cloud cost research

Direct answer

This is the ByteCosts research index: 17 interactive data stories on what AI and cloud actually cost, written from the committed ByteCosts pricing dataset. Each deep-dive pairs an interactive scrollytelling article with a crawlable summary page, and every quantitative claim is source-backed or labeled as modeled. Use this page to find the cost pattern you are about to budget for - per-user unit economics, subscription break-evens, caching, GPU rent-vs-own, platform bills - then open the matching calculator and replace the example assumptions with your own workload. The full list, grouped by topic, is in the static HTML before JavaScript runs.

What this index is

ByteCosts publishes 17 research deep-dives built from the same committed pricing data that powers the calculators. Each piece below links to a summary page with the article's method, sources, and citation block, plus the interactive data story.

Every article follows the same honesty rule: numbers are derived from committed source-backed rates, externally cited, or explicitly labeled as modeled scenarios.

How to use the research

Pick the cost pattern closest to the decision you are making
Read the summary page first; open the interactive story for the full walkthrough
Bring the pattern back to a ByteCosts calculator and swap in your own usage
Cite the summary page, not the interactive file - it carries the canonical URL

Frequently asked questions

How is this different from the ByteCosts blog?

The research index lists the interactive data-story deep-dives. The blog at /blog carries editorial posts and analysis written around the same dataset.

Are the numbers in these articles real prices?

Each article states its basis: figures are committed-data-derived, externally cited, or labeled as modeled. The per-article summary page lists sources and method.