Decentraland vs OpenLedger — how do they compare? Decentraland trades at Rp1,266 (market cap Rp2,51T, Rp181,29M 24h volume), while OpenLedger trades at Rp2,683 (market cap Rp828,74M, Rp87,4M 24h volume). The key difference: Decentraland is far larger — about 3028.7× OpenLedger's market cap, and OpenLedger's supply is capped (309,6M / 1B OPEN (31%)) while Decentraland's keeps growing. Which is the better fit depends on your goals — on Pluang, investors hold Decentraland for 151 Days and OpenLedger for 22 Days on average.
| MANA | OPEN | |
|---|---|---|
Market Cap | Rp2,51T | Rp828,74M |
Volume (24h) | Rp181,29M | Rp87,4M |
Circulating Supply | 2B MANA | 309,6M / 1B OPEN (31%) |
Typical Hold Time | 151 Days | 22 Days |
Signals from Pluang's Aura AI — not financial advice
MANA is trading at Rp1,265 with a bearish technical signal, as moving averages indicate selling pressure while oscillators are neutral. The current price sits near key support at Rp1,253, with resistance at Rp1,267. Market cap stands at Rp2.5T, with a hold time of 151 days suggesting moderate holding behavior. No major protocol or ecosystem updates were noted in recent crypto-specific news.
Overall outlook remains cautious due to bearish technicals, but neutral RSI levels offer some stability. Key opportunities include potential rebounds from support zones, while risks involve continued downtrend pressure and low trading volume volatility. Investors should monitor network activity for fundamental catalysts.
No Aura AI signal available yet.
What Pluang investors did over the last 30 days
Decentraland (MANA) is a decentralized 3D virtual reality platform powered by the Ethereum blockchain where users can create virtual structures such as casinos, art galleries, concert halls and theme parks, and charge other players to visit them. MANA tokens can also be used to pay for a range of avatars, wearables, names, and more on the Decentraland marketplace.
Read more on MANA →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 →