Everscale vs io.net — how do they compare? Everscale trades at Rp169.86 (market cap Rp334,77M, Rp2,11M 24h volume), while io.net trades at Rp2,875 (market cap Rp1,05T, Rp339,34M 24h volume). The key difference: io.net is far larger — about 3136.5× Everscale's market cap, and io.net's supply is capped (365,5M / 800M IO (46%)) while Everscale's keeps growing. Which is the better fit depends on your goals — on Pluang, investors hold Everscale for 5 Days and io.net for 33 Days on average.
| EVER | IO | |
|---|---|---|
Market Cap | Rp334,77M | Rp1,05T |
Volume (24h) | Rp2,11M | Rp339,34M |
Circulating Supply | 2B EVER | 365,5M / 800M IO (46%) |
Typical Hold Time | 5 Days | 33 Days |
Signals from Pluang's Aura AI — not financial advice
No Aura AI signal available yet.
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.
What Pluang investors did over the last 30 days
No sentiment data available yet.
Everscale is a secure and fast layer-one blockchain designed to be a decentralized platform for high-performance applications with real-world relevance, such as stablecoins, CBDCs, DEXs, bridges, Gaming platforms, and more.
Read more on EVER →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 →