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AI forecasts

We Asked AI Which Coin Will Finish October 2026 on Top: XRP, Solana, Hyperliquid, or NEAR?

Two AI models favored XRP and one picked Solana, but their October 2026 forecasts are not the month-end result. Compare all four projections and the catalysts behind them.

By TheFinanceBase Team 4 min read
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There is no confirmed winner yet. In an October 3, 2026 report by Sam Daodu, ChatGPT and Grok picked XRP to finish October ahead of Solana, Hyperliquid, and NEAR; Claude picked Solana. Those are competing model forecasts, not measured returns or reliable odds. October is still underway, so the month-end ranking remains unknown.

What each AI model forecast

Daodu’s report listed approximate starting prices for the four tokens and each model’s estimated October move. The target prices below are the report’s projections, not observed prices or guarantees.

Asset Approximate starting price in the report ChatGPT estimate Claude estimate Grok estimate Reported model ranking
XRP $1.50 +20% to $1.80 +8% to $1.62 +14% to $1.71 ChatGPT and Grok favor XRP
Solana (SOL) $118 +18% to $139 +12% to $132 +9% to $129 Claude’s top pick
Hyperliquid (HYPE) $87 +14% to $99 +3% to $90 +3% to $90 All three place it third
NEAR $5.27 +8% to $5.69 -12% to $4.64 -16% to $4.43 All three place it last

The projections disagree most sharply on NEAR: ChatGPT expected a gain while Claude and Grok projected declines. XRP gets the most votes for first place, but that is a two-model plurality, not proof that XRP has led the market or will end the month on top.

How to read the reported confidence figures

Daodu’s article attributes a 55% chance of XRP leading to ChatGPT and 58% to Grok; Claude assigned Solana a 45% chance. These are figures reported as model outputs, not calibrated probabilities verified against past forecasts. They should not be interpreted as independently established odds.

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Why XRP and Solana were the leading picks

XRP: a forecast tied to a corporate and listing catalyst

The October 3 report pointed to Evernorth’s anticipated merger and planned XRPN Nasdaq trading as potential catalysts. At the time of publication, the merger was expected to finalize on October 7 and trading to begin on October 8, subject to completion of the deal and listing conditions. Those dates were expectations, not confirmation that either milestone occurred. A forecast relying on them could be weakened or invalidated if the transaction or listing were delayed, changed, or failed to happen.

Solana: fund flows and an upgrade story, with timing uncertainty

The report cited 11 consecutive weeks of Solana ETF inflows and about $1.5 billion in aggregate flows. Crypto.com’s September 29 outlook, attributing its figures to SoSoValue, reported $188.2 million in Solana fund inflows for the week ending September 25 and combined assets of around $1.5 billion. These are reported U.S. fund-flow figures; they do not establish that SOL’s price will rise or that flows will continue.

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That same September 29 outlook said the XRP Ledger Batch upgrade schedule had slipped. It described Solana’s Alpenglow upgrade as targeting roughly 150-millisecond finality on a test network, with no confirmed Solana mainnet date. A test-network target is not a demonstrated mainnet result, and an upgrade’s timing or delivery could affect the investment case.

What the other two forecasts imply

Hyperliquid: buybacks are not a price guarantee

All three models placed HYPE third. Daodu’s article cited whale selling and a “sell-the-news” interpretation of a Binance listing as potential risks; the latter was a characterization attributed to Grok, not an independently established explanation of price action.

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In a presentation filed with the SEC, Hyperliquid Strategies said buybacks represented about 99% of net protocol fees and reported that the company acquired 16.5 million HYPE for $773 million during its fiscal year ended June 30, 2026. Those are issuer-presentation claims tied to a stated historical period. They describe reported activity, not evidence that buybacks will determine HYPE’s October performance.

NEAR: distinguish a service exploit from a blockchain compromise

Daodu’s article reported that a bug affecting NEAR Intents led to a $3.8 million exploit and a 9.5% one-day fall in NEAR’s price on October 1. The article said the affected service—not the NEAR blockchain itself—was involved, and that the bug had been fixed and affected users offered compensation. Those incident and remediation details are attributed to that report; they are not independently confirmed here. The article also described a recent NEAR price surge as a possible source of profit-taking pressure.

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What would establish the actual October winner?

The forecasts cannot answer that question. A fair month-end comparison needs a common price source and a consistent measurement convention: for example, each token’s U.S.-dollar price at the same October opening timestamp compared with its price at the same month-end timestamp. The percentage return for each asset would then be calculated from those two observations. Comparing different exchanges, currencies, or cut-off times could produce a different ranking.

The October 3 report did not provide a synchronized independent price series for all four assets from a shared October starting point through month-end. It therefore does not establish which coin was leading as of publication, let alone which one would finish first.

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How much weight should a reader give these forecasts?

  • Treat them as a snapshot of model opinion. The forecasts are attributed estimates based on approximate starting prices, not verified performance records.
  • Watch whether the cited catalysts actually occur. The XRP merger and listing dates were conditional expectations; fund-flow reports describe past flows; and the cited Solana finality figure was a test-network target.
  • Separate an individual service incident from a whole network. The NEAR account concerns NEAR Intents and should not be described as evidence that the entire NEAR blockchain was compromised.
  • Do not infer a complete fundamentals ranking. The available figures do not provide a comparable set of current supply, valuation, unlock, and demand data for all four tokens.

Crypto prices can move sharply, and a model’s projected percentage gain is not a measure of the risk of losing money. The reported split—two models choosing XRP and one choosing Solana—does not establish the eventual October result.

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