Definition
A Data Vending Machine is an on-demand computation marketplace defined by NIP-90. The spec sums it up as "money in, data out": a user publishes a request for some work, multiple service providers compete to fulfill it, and the user pays for a result, frequently over Lightning. It turns Nostr into an open, permissionless job market for tasks like transcription, translation, summarization, and AI inference.
How the protocol is structured
Three bands of event kinds organize the flow. Job requests use kinds 5000-5999 and carry input data plus a maximum bid in millisatoshis. Job results use kinds 6000-6999, where the result kind is exactly 1000 higher than its request. Job feedback uses kind 7000 to signal status such as payment-required, processing, error, or success. Inputs can be raw text, URLs, other Nostr events, or even the output of a previous job, which enables "job chaining" pipelines like transcribe-then-summarize.
Payment and competition
Providers typically attach a Lightning bolt11 invoice or accept a zap on the result event. Some demand payment up front; others deliver first. Because anyone can run a provider, the model is inherently competitive and censorship-resistant: no single vendor gatekeeps the work, and the buyer chooses among results.
For sovereign builders this is a way to buy compute without an account or API key tied to a single corporation. It pairs naturally with on-chain payment rails; see Nostr Marketplace (NIP-15) for goods commerce and Nostr Event Kind for how these kind ranges are interpreted.
In Simple Terms
A Data Vending Machine is an on-demand computation marketplace defined by NIP-90. The spec sums it up as “money in, data out”: a user publishes…