Solana’s memecoin trading registered $13.9 billion in monthly volume last month, the lowest print since February 2024, when the mania hadn’t yet caught fire.
At the same time, Polymarket clocked $3.7 billion in volume, its best month since launch, while Kalshi posted $4.25 billion in volume, its second-best performance. Together, the two largest prediction platforms moved nearly $8 billion, equal to 57% of Solana’s memecoin churn.
That ratio sat below 10% as recently as August. By October, it had crossed 45%. Now it’s breached the majority territory.
The question isn’t solely whether liquidity has rotated, but whether prediction markets represent a structural upgrade in where crypto capital hunts edge, or whether they’re just the next trench in an endless cycle of hot money chasing narrative.
Memecoin fade
Solana memecoin volume peaked in January at $169.5 billion, propelled by hyper-liquid coin flips and influencer-driven token launches.
The velocity was absurd: traders cycled through dozens of new tickers daily, riding momentum that evaporated as soon as the next launch dropped.
Since then, the numbers have gradually started decreasing. In July, memecoin activity on Solana moved $34.4 billion.
August pulled back to $29.2 billion. September fell to $19.7 billion. October landed at $16.5 billion. November’s $13.9 billion represents a 60% collapse from July.
The shape of the decline matters. This wasn’t a single capitulation event, no rug pull or exploit that scared participants out of the market overnight. Instead, volume eroded steadily, suggesting that traders actively chose to redeploy capital rather than flee risk entirely.
The memecoin trade didn’t blow up, but rather exhausted itself.
At the same time, prediction markets accelerated. Kalshi and Polymarket combined for $1.8 billion in July, $1.9 billion in August, $4.1 billion in September, and $7.4 billion in October before hitting $8 billion in November.
The trajectory inverted that of Solana memecoins, which leaked liquidity month after month, while prediction markets doubled, then doubled again.
Information as infrastructure
Vitalik Buterin framed prediction markets as “info finance,” an infrastructure designed to extract signal from crowd behavior rather than pure speculation on reflexive price action.
The distinction feels subtle but carries weight. Memecoins produce no information, as they are driven by hype and often reflect insider positioning.
Prediction markets, at least in theory, aggregate dispersed knowledge into probabilistic forecasts that markets, institutions, and even governments can use.
Buterin argued that artificial intelligence would “turbocharge” prediction markets over the next decade, plugging machine learning models into event contracts and decentralized autonomous organizations that govern market design.
That creates a feedback loop: better models produce tighter spreads, tighter spreads attract more liquidity, and more liquidity refines the signal. Memecoins have no equivalent path to utility. They either maintain momentum or they die.
Thomas Peterffy, founder of Interactive Brokers, went further. He told Finance Magnates that prediction markets would eventually surpass equities in size, estimating a 15-year horizon.
Coming from the chair of a listed brokerage, that’s not hype, but a bet on structural adoption.
If prediction markets scale to the level of equity-market liquidity, the $8 billion they moved in November represents a rounding error compared to what’s coming.
Edge migration
The mechanics of the rotation explain why it happened so fast. Memecoin trading rewarded timing and social positioning: who knew about the launch, who had the best bot setup, who could front-run the crowd.
Prediction markets reward information asymmetry of a different kind: understanding voter turnout models better than the average participant, reading geopolitical risk faster than cable news, or interpreting Federal Reserve signals before they move bond markets.
Haseeb Qureshi of Dragonfly Capital pointed out that Polymarket called the US presidential election before major networks, assigning President Donald Trump a 97% probability by midnight Eastern while TV anchors hedged on swing states.
That wasn’t luck, but a reflection of aggregated participant knowledge outpacing institutional media. Google’s decision to integrate Polymarket odds into search results legitimized the platform overnight, flipping perception from “sketchy offshore casino” to “clearest source of truth,” as Qureshi noted.
For traders who left Solana memecoins, prediction markets offer a narrative they couldn’t find in dog-themed tokens: the possibility that their bets yield valuable signals.
They’re still gambling, but the gamble pretends to generate knowledge, and that psychological shift matters. A trader who loses money on a memecoin admits they got dumped on.
A trader who loses money on a prediction market can claim they misjudged probabilities but participated in price discovery.
What stays unresolved
Liquidity depth, while growing, doesn’t yet support institutional-scale positioning without slippage. And the markets themselves remain vulnerable to manipulation: a sufficiently motivated actor with enough capital can distort probabilities, especially on low-volume contracts.
Additionally, the market’s subject can influence its results. Brian Armstrong recently said words that were the subject of a prediction market during a Coinbase earnings call. The episode sparked debate over concerns about manipulation.
Memecoins, meanwhile, haven’t disappeared. The $13.9 billion in monthly volume still dwarfs most DeFi protocols and rivals the trading activity of mid-cap centralized exchanges.
The participants who remain likely represent a harder core, traders who prefer pure price action over probabilistic modeling, or who simply don’t care about the intellectual cover that prediction markets provide.
The rotation doesn’t prove that prediction markets will absorb all speculative crypto capital. It demonstrates that when participants decide they want the edge rather than momentum, they’ll move.
Whether that edge proves real or imagined will determine whether prediction markets grow into the equity-scale venue Peterffy envisions, or become the next exhausted trade. For now, the liquidity speaks: the trenches moved, and $8 billion followed.
