OLAXBT vs io.net — how do they compare? OLAXBT trades at Rp725.83 (market cap Rp167,47M, Rp16,21M 24h volume), while io.net trades at Rp2,002 (market cap Rp765,51M, Rp400,7M 24h volume). The key difference: io.net is far larger — about 4.6× OLAXBT's market cap, and OLAXBT's circulating supply is 230,3M / 1B AIO (24%) versus 381,5M / 800M IO (48%) for io.net. Which is the better fit depends on your goals — on Pluang, investors hold OLAXBT for 3 Days and io.net for 34 Days on average.
| AIO | IO | |
|---|---|---|
Market Cap | Rp167,47M | Rp765,51M |
Volume (24h) | Rp16,21M | Rp400,7M |
Circulating Supply | 230,3M / 1B AIO (24%) | 381,5M / 800M IO (48%) |
Typical Hold Time | 3 Days | 34 Days |
Signals from Pluang's Aura AI — not financial advice
No Aura AI signal available yet.
IO token trades at Rp 2,004, showing bearish technical signals with 18 sell indicators and strong selling pressure from moving averages. The price is near the pivot point of Rp 2,028, with support at Rp 1,954 and resistance at Rp 2,107. Circulating supply is 48% of max, with an average hold time of 34 days, indicating moderate network participation.
Overall outlook is cautious due to bearish momentum and neutral fundamentals. Key opportunities include potential rebounds from oversold RSI levels, while risks involve low liquidity and high volatility. Investors should monitor support breaks and ecosystem updates for directional cues.
What Pluang investors did over the last 30 days
OLAXBT is a decentralized AI trading platform that enables users to build and deploy automated trading agents through a modular, no-code infrastructure. Powered by its proprietary AIO Nexus Data Layer and Model Context Protocol (MCP), it supports real-time data access, standardized execution, and scalable agent interactions. The AIO token fuels payments, feature access, staking, and future governance within the ecosystem.
Read more on AIO →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 →