Bitcoin trades amid $153M crypto long liquidations in 24h

$153M long liquidations reflect a broad, leverage-driven market flush

For scale, large liquidation days are not unusual during periods of elevated leverage. As reported by Investing.com, a separate 24-hour drawdown earlier this cycle saw roughly $740 million in crypto liquidations, largely from long positions, underscoring how quickly leverage can unwind at scale.

As reported by Bitcoin Magazine, another session recorded about $713 million in long positions liquidated during a sharp downswing. Against that backdrop, the current wipeout sits within the lower band of recent liquidation spikes, but it still denotes a meaningful clearing of leveraged longs.

Key drivers: leverage risk, funding rates, and open interest

Liquidation cascades typically reflect a build-up of directional leverage and crowded positioning. When funding rates signal persistent long bias and open interest expands without a commensurate increase in spot demand, the market becomes prone to abrupt deleveraging once price momentum turns.

For editorial clarity, the core claim around this move is captured by trade-press coverage. As reported by BitcoinWorld (publication): “Massive Crypto Liquidations: Over $153M Longs Wiped Out Across ETH, BTC, SOL.”

Mechanically, once initial margin levels are breached, exchanges auto-deleverage long positions, which can accelerate price slippage and trigger additional forced sales. Elevated funding and large open interest are not deterministic causes, but together they describe conditions under which long-liquidation waves can propagate more quickly across BTC and ETH perps and futures.

How to verify the $153M figure across reputable dashboards

Independent validation benefits from cross-checking multiple analytics providers, as methodologies differ by exchange coverage, instrument scope, and time windows. Based on data from CoinGlass, users can review rolling 24-hour liquidation totals, filter for long positions, and observe asset-level contributions for BTC and ETH.

Methodological nuances matter. Glassnode’s datasets may emphasize on-chain and derivatives-linked metrics using distinct sampling windows, while Kaiko focuses on market microstructure and derivatives order book activity; figures can diverge due to venue inclusion, treatment of perpetuals versus dated futures, and whether the tally is a UTC-fixed window or a rolling 24-hour snapshot.

For consistency, align time zones, confirm whether totals are net or side-specific (long-only versus combined liquidations), and match the same lookback across providers. Figures can update intraday as exchanges publish new liquidation events, so a small variance across dashboards is expected rather than anomalous.