0G (0G) is tracked by TokenRadar as a Artificial Intelligence (AI), Infrastructure, Smart Contract Platform, BNB Chain Ecosystem asset. The 0G protocol is Web3’s largest deAIOS and L1 ecosystem; infinitely scalable infrastructure comprised of an L1 (EVM) modular blockchain, low cost/ultra fast storage, verifiable AI compute, generative agents, AI Data availability (DA), and a unified service m 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 This overview focuses on market structure, historical reference points, liquidity, and risk context rather than buy or sell recommendations.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 | $0.5414 |
| Market Cap | $115.43M |
| 24h Change | -2.64% |
| Market Rank | #268 |
| 24h Volume | $9.73M |
| ATH Distance | -92.33% |
Market Position for 0G
0G trades at $0.5414 with a market cap of $115.43M and 24h volume of $9.73M. The latest ranked market snapshot places 0G at #268 by market capitalization. The token is -92.33% from its all-time high of $7.05, recorded on September 23, 2025. Its all-time low is $0.4551, recorded on February 6, 2026, while the 30-day move is -8.74%. Circulating supply is 213,199,722, total supply is 1,000,000,000, and max supply is not available. The volume-to-market-cap ratio is 8.43%, 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 0G a risk score of 6/10, a growth potential index of 39/100, narrative strength of 95/100, and a volatility index of 37/100. The computed risk level is medium. 0G is a strong narrative, near ATH token.
Risk should be read together with liquidity. 0G has 24h high and low levels of $0.5606 and $0.5360, so the short-term range is visible before considering broader 7-day and 30-day changes of -2.46% and -8.74%.
Historical Data Points
The historical reference set for 0G includes an all-time high of $7.05 on September 23, 2025, an all-time low of $0.4551 on February 6, 2026, and a 1-year move of +0.00%. 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 213,199,722, total supply is 1,000,000,000, and max supply is not available. Fully diluted valuation is $541.41M. 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
0G 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 0G?
The 0G protocol is Web3’s largest deAIOS and L1 ecosystem; infinitely scalable infrastructure comprised of an L1 (EVM) modular blockchain, low cost/ultra fast storage, verifiable AI compute, generative agents, AI Data availability (DA), and a unified service m
Is 0G a low-risk asset?
No crypto asset should be treated as low risk by default. TokenRadar currently shows a risk score of 6/10, and that score should be checked against volatility, liquidity, supply, and recent events.
What market data matters most for 0G?
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 0G?
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 0G 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.
0G also needs category-aware interpretation. A Artificial Intelligence (AI) 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 0G 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.
0G also needs category-aware interpretation. A Artificial Intelligence (AI) 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 0G 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.
