Falcon Finance vs io.net — how do they compare? Falcon Finance trades at Rp1,225 (market cap Rp3,63T, Rp1,14T 24h volume), while io.net trades at Rp2,876 (market cap Rp1,06T, Rp338,23M 24h volume). The key difference: Falcon Finance is far larger — about 3.4× io.net's market cap, and Falcon Finance's circulating supply is 3B / 10B FF (30%) versus 365,5M / 800M IO (46%) for io.net. Which is the better fit depends on your goals — on Pluang, investors hold Falcon Finance for 7 Days and io.net for 33 Days on average.
| FF | IO | |
|---|---|---|
Market Cap | Rp3,63T | Rp1,06T |
Volume (24h) | Rp1,14T | Rp338,23M |
Circulating Supply | 3B / 10B FF (30%) | 365,5M / 800M IO (46%) |
Typical Hold Time | 7 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
Falcon Finance is developing a universal collateral infrastructure that transforms any liquid asset—such as digital assets, currency-backed tokens, and tokenized real-world assets—into USD-pegged on-chain liquidity. The native token of the protocol, FF, serves as a gateway to governance, staking rewards, community incentives, and exclusive access to unique products and features.
Read more on FF →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 →