Artificial intelligence models ChatGPT and Claude have issued conflicting price predictions for the XRP cryptocurrency after the asset fell to approximately $1.45 [1].
These forecasts highlight the volatility of the digital asset market and the varying ways AI interprets historical data to predict future value. As investors look for stability, the wide gap between these two leading AI models underscores the uncertainty surrounding XRP's trajectory.
ChatGPT predicts a bullish outlook for the token. The AI targets a price range between $2.50 and $3.50 for XRP by late 2026 [2], which represents an upside of up to 155% from current levels [2]. Some reports specify a single point target of $3.50 [1].
In contrast, Claude provides a more pessimistic forecast. The model warns that XRP could fall to $0.90 [1]. Other data indicates Claude predicts the price will be $0.95 by April 30, 2026 [3].
Market data shows XRP recently hit a peak of $1.50 before pulling back to $1.45 [1]. Current price reports vary across platforms, with Blockonomi reporting $1.47 [2] and AOL reporting $1.40 [4]. This volatility follows a significant 62% decline from a July 2025 peak of $3.65 [4].
Broader market trends also show instability. Bitcoin is currently priced at $66,000, down 48% from its high of $126,000 [4]. However, Bitcoin did move past $78,000 on April 17 after the Strait of Hormuz reopened [2].
Additional AI analysis suggests a short-term dip. AI agents expect XRP to drop about four percent over the next 60 days [3]. Despite this, some reports note fresh weekly inflows into XRP of $119 [2].
"ChatGPT sees XRP climbing to $3.50, while Claude warns it could fall to $0.90," 247WallSt said [1].
“ChatGPT now targets $2.50 to $3.50 for XRP by late 2026”
The stark contradiction between ChatGPT and Claude's predictions illustrates the limitations of using generative AI for financial forecasting. Because these models process market data differently, they can produce wildly different outcomes, one bullish and one bearish, based on the same set of volatile market conditions. This suggests that AI-generated price targets should be viewed as data-driven simulations rather than reliable financial advice.
