AI Models Forecast October Performance for Major Cryptocurrencies; XRP and Solana Lead Competing Predictions

Three artificial intelligence models analyzed four cryptocurrencies to predict October performance, with ChatGPT and Grok favoring XRP while Claude predicted Solana would lead. All three models ranked NEAR last after the token dropped 9.5% following a $3.8 million security exploit, while they positioned Hyperliquid in third place. The forecasts reflected cautious optimism, with confidence levels below 60 percent across all top predictions.
Three leading artificial intelligence systems—ChatGPT, Claude, and Grok—conducted a comparative forecasting exercise on four digital assets heading into October 2026. The models demonstrated substantial disagreement on performance rankings, with two systems backing XRP while the third favored Solana. Their predictions incorporated significant market events, including a planned merger and a week-long streak of exchange-traded fund purchases totaling $1.5 billion. Notably, all three systems expressed low confidence in their top selections, with success probabilities remaining below 60 percent.
NEAR Protocol faced immediate headwinds when a security vulnerability in an associated cross-chain platform resulted in a $3.8 million loss during the month's opening days. The incident triggered sharp single-day selling pressure, though analysts noted the breach affected a supporting service rather than the core blockchain network. The cryptocurrency had experienced exceptional growth in the preceding month, raising questions about whether price corrections were inevitable regardless of the security event.
AI-generated cryptocurrency forecasts may influence retail investment decisions, potentially directing capital toward assets these models recommend. Since the models expressed cautious outlooks with below-60-percent confidence levels, their limited predictive certainty could either discourage speculative trading or encourage risk-aware positioning. Retail investors relying on AI analysis without independent research face exposure to volatile digital assets, while institutional participants might view such forecasts as indicators of broader sentiment rather than reliable predictions.