Ontology (ONT) is tracked by TokenRadar as a Smart Contract Platform, Masternodes, Proof of Stake (PoS), Made in China asset. Ontology is a new high-performance public blockchain project & a distributed trust collaboration provides new high-performance public blockchains that include a series of complete distributed ledgers and smart contract systems. Data snapshot date: May 14, 2026. This overview focuses on market structure, historical reference points, liquidity, and risk context rather than buy or sell recommendations.
| Metric | Value |
|
|
|
| Price | $0.0622 |
| Market Cap | $62.24M |
| 24h Change | -3.27% |
| Market Rank | #436 |
| 24h Volume | $10.63M |
| ATH Distance | -99.43% |
Market Position for ONT
Ontology trades at $0.0622 with a market cap of $62.24M and 24h volume of $10.63M. The latest ranked market snapshot places ONT at #436 by market capitalization. The token is -99.43% from its all-time high of $10.92, recorded on May 3, 2018. Its all-time low is $0.0391, recorded on March 9, 2026, while the 30-day move is -21.96%. Circulating supply is 1,000,000,000, total supply is 1,000,000,000, and max supply is not available. Ontology has a recorded genesis date of February 26, 2018. The volume-to-market-cap ratio is 17.08%, which helps separate active markets from thin markets. A higher ratio usually means recent trading activity is easier to observe, while a very low ratio can make price changes less reliable as a signal.
TokenRadar Risk Context
TokenRadar currently assigns Ontology a risk score of 8/10, a growth potential index of 70/100, narrative strength of 30/100, and a volatility index of 100/100. The computed risk level is high. Ontology is a high-risk, high growth potential, near ATH token.
Risk should be read together with liquidity. Ontology has 24h high and low levels of $0.0649 and $0.0609, so the short-term range is visible before considering broader 7-day and 30-day changes of -0.96% and -21.96%.
Historical Data Points
The historical reference set for ONT includes an all-time high of $10.92 on May 3, 2018, an all-time low of $0.0391 on March 9, 2026, and a 1-year move of -63.56%. These figures do not predict the future, but they show whether the current price is near extremes or in a middle range.
Supply and Valuation
Circulating supply is 1,000,000,000, total supply is 1,000,000,000, and max supply is not available. Fully diluted valuation is $62.24M. Market cap and FDV can diverge when a large portion of supply is not circulating, so investors should compare circulating supply, total supply, and unlock or emission information before relying on valuation multiples.
What Could Change the Setup
Ontology would need stronger evidence across volume, liquidity, development activity, and category momentum for the setup to improve. Weak follow-through, falling volume, large unlocks, contract migrations, or negative security events would weaken the research case even if the spot price rises for a short period.
FAQ
What is Ontology?
Ontology is a new high-performance public blockchain project & a distributed trust collaboration provides new high-performance public blockchains that include a series of complete distributed ledgers and smart contract systems.
Is ONT a low-risk asset?
No crypto asset should be treated as low risk by default. TokenRadar currently shows a risk score of 8/10, and that score should be checked against volatility, liquidity, supply, and recent events.
What market data matters most for ONT?
The most useful starting points are price, market cap, 24h volume, market rank, ATH distance, circulating supply, and the 30-day trend.
Does this overview recommend buying Ontology?
No. It is a structured research summary for comparing data points and risks.
Disclaimer: This article is for informational purposes only and does not constitute financial advice. Always do your own research (DYOR).
For ONT research, the important control is consistency between the live market snapshot and the longer historical record. A single 24h move can be noisy, while market cap rank, 30-day performance, all-time high distance, supply structure, and volume-to-cap ratio create a more durable comparison set. This is why the article separates market data from decision rules and keeps the conclusion conditional.
Ontology also needs category-aware interpretation. A Smart Contract Platform token with high liquidity can behave very differently from a low-volume asset with the same percentage move. The practical question is whether volume, spread quality, supply data, and catalyst evidence confirm the move or contradict it.
The safest way to use this overview article is as a checklist. Confirm the latest price, check the current rank, compare 24h volume with market cap, review the ATH and ATL dates, and look for any project-specific changes before treating the data as current enough for research.
For ONT research, the important control is consistency between the live market snapshot and the longer historical record. A single 24h move can be noisy, while market cap rank, 30-day performance, all-time high distance, supply structure, and volume-to-cap ratio create a more durable comparison set. This is why the article separates market data from decision rules and keeps the conclusion conditional.
Ontology also needs category-aware interpretation. A Smart Contract Platform token with high liquidity can behave very differently from a low-volume asset with the same percentage move. The practical question is whether volume, spread quality, supply data, and catalyst evidence confirm the move or contradict it.
The safest way to use this overview article is as a checklist. Confirm the latest price, check the current rank, compare 24h volume with market cap, review the ATH and ATL dates, and look for any project-specific changes before treating the data as current enough for research.
For ONT research, the important control is consistency between the live market snapshot and the longer historical record. A single 24h move can be noisy, while market cap rank, 30-day performance, all-time high distance, supply structure, and volume-to-cap ratio create a more durable comparison set. This is why the article separates market data from decision rules and keeps the conclusion conditional.
Ontology also needs category-aware interpretation. A Smart Contract Platform token with high liquidity can behave very differently from a low-volume asset with the same percentage move. The practical question is whether volume, spread quality, supply data, and catalyst evidence confirm the move or contradict it.
