io.net vs OpenLedger — how do they compare? io.net trades at Rp2,882 (market cap Rp1,06T, Rp338,23M 24h volume), while OpenLedger trades at Rp2,676 (market cap Rp828,74M, Rp87,4M 24h volume). The key difference: io.net is far larger — about 1279.1× OpenLedger's market cap, and io.net's circulating supply is 365,5M / 800M IO (46%) versus 309,6M / 1B OPEN (31%) for OpenLedger. Which is the better fit depends on your goals — on Pluang, investors hold io.net for 33 Days and OpenLedger for 22 Days on average.
| IO | OPEN | |
|---|---|---|
Market Cap | Rp1,06T | Rp828,74M |
Volume (24h) | Rp338,23M | Rp87,4M |
Circulating Supply | 365,5M / 800M IO (46%) | 309,6M / 1B OPEN (31%) |
Typical Hold Time | 33 Days | 22 Days |
Signals from Pluang's Aura AI — not financial advice
IO token trades at Rp2,893 with a market cap of Rp1.06 trillion, showing bearish technical signals from moving averages and ADX indicators. The token has a circulating supply of 365.5 million out of 800 million, with an average hold time of 33 days. Recent news is unrelated to the token's ecosystem, indicating no direct fundamental updates affecting its value.
Overall outlook remains cautious due to bearish technicals and neutral oscillators. Key opportunities include potential rebounds from support levels near Rp2,575, while major risks involve high volatility and lack of recent protocol developments. Investors should monitor trading volume and on-chain activity for signs of recovery.
No Aura AI signal available yet.
What Pluang investors did over the last 30 days
io.net, formerly known as ANTBIT, leverages a decentralized computing network powered by Solana and Aptos to provide machine learning engineers with access to distributed cloud clusters. It aims to address challenges like limited availability, poor choice, and high costs associated with accessing GPUs in the public cloud.
Read more on IO →OpenLedger is an AI blockchain that unlocks liquidity for monetizing data, models, applications, and agents. It facilitates the training, deployment, and on-chain tracking of specialized AI models and data, addressing critical challenges related to transparency, attribution, and verifiability in AI.
Read more on OPEN →