Hyperliquid Liquidation Map: Real Liquidation Levels (2026)

The short version: on Hyperliquid every open position, its size and its liquidation price are public, so you can build a liquidation map from real data instead of the estimated heatmaps most sites show. In our snapshot of 2 November 2026 (08:22 UTC), the 300 largest accounts on the leaderboard held no liquidation level within 10% of the mark price on BTC, ETH, HYPE or SOL. The closest big level was a $113.4M BTC short liquidating at $88,241, 13.0% above the $78,121 mark, and a $118.8M HYPE long liquidating at $74.61, 13.3% below the $86.04 mark.

"Liquidation map" and "liquidation heatmap" are some of the most searched terms in crypto derivatives. Traders want to know where forced selling or forced buying would start if price moves. On centralized exchanges those charts are estimates: positions are private, so tools guess liquidation prices from open interest and assumed leverage. Hyperliquid is different because its order book and clearinghouse live on-chain. This guide explains what a liquidation map is, why on-chain data changes the picture, how to read a real dated example, what the map cannot tell you, and ends with a Python script that builds your own map with no account and no API key.

What a liquidation map shows

A liquidation map groups open positions by the price at which they would be force-closed. Longs liquidate below the current price, shorts above it. If a lot of notional sits at one level, a move to that level can trigger a chain of market orders from the liquidation engine, which pushes price further and can trigger the next level. That chain is what traders call a liquidation cascade.

The useful questions are simple:

• How much notional would be liquidated within 5%, 10% or 20% of the current price?
• Is that notional mostly longs (downside fuel) or shorts (upside fuel)?
• Is it spread across many wallets or concentrated in one or two accounts?

If you need the mechanics of how a single liquidation price is calculated first, start with our Hyperliquid liquidation price guide.

Estimated heatmaps vs on-chain liquidation data

Most liquidation heatmaps you see online work backwards: they take open interest changes, assume a mix of leverage settings (for example 10x, 25x, 50x, 100x) and project where those positions would liquidate. The result can look precise, but every band is a model output, not an observed position.

On Hyperliquid you can read the real thing. The public clearinghouseState info endpoint returns, for any address, each open position with its size, entry price, position value, margin mode and the liquidationPx the protocol currently computes. Add the mark price from metaAndAssetCtxs and you know exactly how far each position is from liquidation.

The limit is coverage, not accuracy. There is no single endpoint that returns every position on the exchange, so in practice you scan a list of addresses. The leaderboard is a convenient list because it covers the accounts that matter most for size. That is what we did below.

A real example: the 300 largest accounts on 2 November 2026

We took the 300 leaderboard accounts with the highest account value, read their clearinghouse state at about 08:22 UTC on 2 November 2026, and measured the distance from each position's liquidation price to the mark price. 73 of the 300 accounts had open perp positions; the rest held spot, vault deposits or idle USDC.

Coin	Mark price	Longs held	Shorts held	Longs liquidating within 20%	Shorts liquidating within 20%
BTC	$78,121	$107.0M (9 positions)	$686.6M (24)	$3.1M	$113.4M
ETH	$2,288.3	$162.7M (17)	$601.7M (19)	$0	$0
HYPE	$86.04	$226.8M (15)	$380.6M (32)	$118.8M	$11.2M
SOL	$94.26	$82.5M (10)	$156.3M (14)	$0	$0

Within 10% of the mark price the answer was zero on all four coins. Widening the band to 50% shows where the deeper levels sit:

• BTC: $92.0M of longs and $187.3M of shorts liquidate within 50%.
• ETH: $140.3M of longs and $45.8M of shorts within 50%. The nearest large ETH level was a $69.3M long liquidating at $1,787.63, 21.9% below the mark.
• HYPE: $182.0M of longs and $110.0M of shorts within 50%.
• SOL: $51.9M of longs within 50%, all from one position liquidating at $68.25 (27.6% below), and no shorts.

Concentration matters more than the total

The two biggest nearby levels each belonged to a single wallet. The $113.4M BTC short at $88,241 was held by 0xfc27…9d9d, and the $118.8M HYPE long at $74.61 by 0x082e…ca88. A map that shows "$113M of shorts at $88K" sounds like a crowd of traders. In this case it was one account. One account can also add margin, reduce size or hedge long before price gets there, which moves the whole band in a single transaction.

Many large positions have no liquidation price at all

For $4.8M of BTC, $6.7M of ETH, $30.3M of HYPE and $12.8M of SOL notional in the sample, the API returned no liquidation price. That happens when the account's collateral is large enough that no realistic price move would liquidate it. These positions never show up on a liquidation map, even though they are real size in the market.

How to read a liquidation map without fooling yourself

1. Check the sample. A map built from 300 big accounts is not the whole market. In our snapshot, BTC open interest was about $3.14B; the sampled positions were a fraction of it.
2. Look at distance, not just size. $100M liquidating 13% away matters much less than $10M liquidating 2% away. Compare the distance with normal volatility: our volatility and ATR guide measured a 14-day ATR of 2.45% for BTC and 4.57% for HYPE at the end of October, so a 13% move is several days of average range.
3. Remember cross margin moves the level. For cross-margin positions the liquidation price depends on the whole account: other positions, unrealized PnL and funding. It changes every time any of those change. Isolated positions are more stable. See isolated vs cross margin.
4. Liquidation is not the only outcome. When a liquidation cannot be absorbed by the book, Hyperliquid can use its liquidator vault and, in extreme cases, auto-deleveraging. Our ADL guide covers that tail.
5. Pair it with positioning data. A liquidation map tells you where forced flow sits; a long/short ratio and open interest tell you how crowded each side is overall.

Using it for your own risk

The most practical use of a liquidation map is not predicting the next candle. It is checking whether your own stop or liquidation price sits next to a cluster. If your long liquidates just under a big long cluster, a cascade through that level can reach you fast, with wider spreads and more slippage than usual. Moving your stop above the cluster, or lowering leverage so your liquidation sits well below it, is often cheaper than finding out the hard way. Our leverage guide and position size calculator help you choose a size that keeps liquidation far from the market.

The second use is following specific wallets. If one account holds a level that the whole market is watching, it is worth watching that account: whether it adds margin, cuts size or flips side. That is exactly the kind of tracking Hyperfolio is built for.

Build your own liquidation map in Python

This script reads the public leaderboard, takes the 300 largest accounts by account value, fetches their positions from the public info API and prints how much long and short notional would liquidate within 5%, 10%, 20% and 50% of the mark price, plus the ten closest levels. It needs only requests, no key and no account.

import requests
from collections import defaultdict
from concurrent.futures import ThreadPoolExecutor

API = "https://api.hyperliquid.xyz/info"
LB = "https://stats-data.hyperliquid.xyz/Mainnet/leaderboard"
TOP_N = 300                      # largest accounts by account value
BANDS = [5, 10, 20, 50]          # % distance from mark price

rows = requests.get(LB, timeout=60).json()["leaderboardRows"]
rows = sorted(rows, key=lambda r: float(r["accountValue"]), reverse=True)[:TOP_N]

def state(addr):
    return requests.post(API, json={"type": "clearinghouseState", "user": addr}, timeout=20).json()

with ThreadPoolExecutor(8) as ex:
    states = list(ex.map(state, [r["ethAddress"] for r in rows]))

meta, ctxs = requests.post(API, json={"type": "metaAndAssetCtxs"}, timeout=20).json()
mark = {u["name"]: float(c["markPx"]) for u, c in zip(meta["universe"], ctxs)}

bands = defaultdict(lambda: defaultdict(float))
nearest = []
for addr, st in zip([r["ethAddress"] for r in rows], states):
    for ap in st["assetPositions"]:
        p = ap["position"]
        if p.get("liquidationPx") is None:
            continue                         # collateral covers the whole move
        coin, liq, ntl = p["coin"], float(p["liquidationPx"]), float(p["positionValue"])
        side = "long" if float(p["szi"]) > 0 else "short"
        m = mark[coin]
        dist = (m - liq) / m * 100 if side == "long" else (liq - m) / m * 100
        nearest.append((dist, coin, side, ntl, liq, addr))
        for b in BANDS:
            if dist <= b:
                bands[coin][(side, b)] += ntl

for coin in ["BTC", "ETH", "HYPE", "SOL"]:
    print(coin, "mark", mark[coin])
    for b in BANDS:
        print(f"  within {b:>2}%  longs ${bands[coin][('long', b)]/1e6:7.1f}M"
              f"  shorts ${bands[coin][('short', b)]/1e6:7.1f}M")
for d, coin, side, ntl, liq, addr in sorted(nearest)[:10]:
    print(f"{coin:5} {side:5} ${ntl/1e6:6.1f}M liq {liq:,.4g} ({d:.1f}% away) {addr[:6]}...{addr[-4:]}")

Change TOP_N to scan more accounts, or replace the leaderboard list with your own watchlist of addresses. Keep the concurrency modest so you stay within the public API rate limits described in our rate limits guide.

Track the wallets behind the levels with Hyperfolio

A liquidation map is a snapshot; the wallets behind it keep moving. Hyperfolio is a free, read-only PWA where you paste any Hyperliquid address and see its open positions, liquidation prices, PnL and funding without connecting a wallet or sharing keys. You can follow several large accounts side by side (see tracking multiple wallets) and spot when one of them changes the picture. If you trade on Hyperliquid yourself, the referral code HYPERFOLIO gives you 4% off trading fees.

FAQ

Does Hyperliquid have an official liquidation map?

No. The exchange exposes the raw data (positions and liquidation prices per address) through its public API, and third-party tools build maps on top of it. Coverage depends on how many addresses each tool scans.

Are Hyperliquid liquidation heatmaps accurate?

Maps built from on-chain positions show real liquidation prices at the moment they were read. Maps built from open interest and assumed leverage, as on most centralized exchanges, are estimates. Always check which method a chart uses.

Why did the liquidation price of a big position change?

For cross-margin accounts the liquidation price depends on all positions, unrealized PnL, funding and deposits in the account, so it shifts whenever any of those change. Isolated positions only change when margin is added or removed or funding is paid.

Why do some positions show no liquidation price?

When the account holds enough collateral that no realistic price would liquidate the position, the API returns no liquidation price. In our 2 November 2026 sample that applied to $30.3M of HYPE notional, for example.

Can a liquidation map predict where price will go?

No. It shows where forced orders would appear if price gets there. Large levels can act as magnets or be defended, and the holder can move them at any time. Use it for risk planning, not as a signal on its own.