OpenAI’s ChatGPT has offered a long-range view on XRP and its chances of reaching $10. The model puts the cumulative probability at 10% by Dec. 31, 2030. That leaves a 90% chance the token does not hit the target in that period. It is not a forecast with certainty, just a probability estimate based on current conditions and assumptions.
ChatGPT’s Year-by-Year View
ChatGPT sees 2030 as the most likely year for XRP to reach $10. The second half of that year is the strongest window. Still, the model gives just a 4.5% probability of a first touch during 2030. The earlier years are lower: 0.5% for the rest of 2026, 1% in 2027, 1.5% in 2028 and 2.5% in 2029. Those numbers add up to a 10% cumulative chance by the end of the decade. I think the takeaway is simple: $10 is possible in theory, but unlikely under the model’s base case.
What Would Need to Happen
At about $1.10, XRP would need a gain of more than 800% to reach $10. With an estimated circulating supply of 63.52 billion tokens, that price would imply a market cap near $635.2 billion. Such a move would likely require large capital inflows. Stronger institutional demand could help. So could sustained interest in spot XRP exchange-traded funds, wider use of Ripple’s payment infrastructure and a long crypto bull market. The risks are just as clear. Weaker institutional demand, competition from other payment networks and digital assets, plus broader market volatility could keep the target out of reach.
Price Chart Still Looks Weak
XRP was trading at $1.08 at press time. That is below its 50-day simple moving average of $1.37 and its 200-day average of $1.27. The 50-day average remains above the 200-day average, but price sits below both. That points to weakening buying pressure. The 14-day relative strength index is 26.51, which puts XRP in oversold territory. Selling pressure has been strong. A short-term relief rebound is possible if buyers return, perhaps, but the oversold reading alone does not confirm a reversal. XRP may stay under pressure until it reclaims those moving averages.
