The DePIN Data Problem

Every AI-compute DePIN advertises a GPU count. io.net says it has tens of thousands of GPUs for AI workloads. But the number most people quote is registered capacity — the GPUs the network believes exist. What actually matters is how many are active and how many are busy. Those are three different numbers, and conflating them is how bad GPU supply data gets born.

At Kairos Signal, we measure the gap between registered and active supply directly from first-party telemetry. It's the single most important number on any compute DePIN, and almost no dashboard publishes it.

Registered vs. Active: The Real GPU Supply

The pattern repeats across the AI-compute sector. Registered device count grows while active count stays flat — a widening pool of idle inventory that looks like growth if you only read the top-line number.

Divide busy by active and you get a fill rate — which will always be high, because it only measures the working pool. Divide busy by registered and you get the true utilization of everything the network claims — which is usually far lower. The two answers to "how utilized is io.net?" are not the same question.

The Utilization Trap

This is where most GPU supply analysis goes wrong. A reported utilization of 96%+ is almost always a fill rate of the active pool — it can barely be anything but high. The number that actually tells you whether the network is absorbing supply is registered-supply utilization, and that's the number that requires good supply data to compute.

Query io.net GPU Supply Yourself

# io.net supply + market data
curl "https://kairossignal.com/v1/networks/io.net" \
  -H "Authorization: Bearer $KS_API_KEY"

The utilization-relevant fields

curl "https://kairossignal.com/v1/networks/io.net?fields=devices_registered,devices_active,gpu_utilization"

Compare GPU utilization methodology across io.net, Akash, and Render

curl "https://kairossignal.com/v1/compare?concept=GPU_UTILIZATION&networks=io.net,akash,render"

Each field carries a verify_url pointing at io.net's own API, so you can confirm the registered and active counts against the source — and see whether "utilization" in the response means fill rate or true registered-supply utilization.

Why Provenance Wins

Because our daily batch is Merkle-rooted and timestamped to Bitcoin via OpenTimestamps, the registered/active gap you read today is provably the gap that existed today. When io.net restates a device count, both the original and revised values stay in the archive with their timestamps — so an agent backtesting on GPU supply never fits on silently-restated data.

A GPU count without a registered/active split is marketing. Ask for the supply data underneath. Get a free API key →

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This is a data product. Kairos Signal publishes no trading signals, performance returns, win rates, or accuracy claims.