10 first-party metrics moved more than 2% in the last 24 hours, on 10 of the networks we read first-party (AKT, IO, PLANCK, SN103, SN117, SN32). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
n₀(5)=14, n₀(6)=16, n₀(11)=27 — correct, machine-checked, and seven weeks late. What we did, what M. Thiim did first, and why we published anyway.
10 first-party metrics moved more than 2% in the last 24 hours, on 8 of the networks we read first-party (IO, KYVE, PLANCK, SN103, SN117, SN13). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
10 first-party metrics moved more than 2% in the last 24 hours, on 9 of the networks we read first-party (AKT, DVPN, IO, SN103, SN11, SN117). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
10 first-party metrics moved more than 2% in the last 24 hours, on 8 of the networks we read first-party (AKT, IO, IPFS, SN117, SN55, SN66). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
9 first-party metrics moved more than 2% in the last 24 hours, on 6 of the networks we read first-party (AKT, IO, IPFS, SN103, SN97, TAO). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
10 first-party metrics moved more than 2% in the last 24 hours, on 9 of the networks we read first-party (AKT, IO, IPFS, LPT, SCP, SN41). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
10 first-party metrics moved more than 2% in the last 24 hours, on 9 of the networks we read first-party (AKT, IO, IPFS, SN32, SN41, SN76). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
10 first-party metrics moved more than 2% in the last 24 hours, on 8 of the networks we read first-party (AKT, IO, IPFS, NODL, SN21, SN82). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
The Akash GPU utilisation figure circulating in DePIN research traces to a single blog post from October 2024 that says 74% in its title and 79% in its body, with no source and no denominator. Akash's own API returns 56.6% today. Here is the full daily series and the one command that checks it.
Where to get free DePIN network data in 2026 — the honest
**Live data:** Streamr (DATA) live telemetry · DEPIN (DEPIN) live telemetry — every value with source, as_of and a verify...