BitMine perpsBMNR

Stock perp · Binance, OKX, Hyperliquid · #153 by volume

17.340-6.12% 24h

Binance USDT · 24h 17.260 – 18.590

24h volume: $28.4M; #153 of 925
Open interest: $12.0M; +1.3% contracts · 24h
Spread: 5.61 bps; median · 24h
Size at best price: $11.3K; mean · 24h
Net taker flow: −$614.7K; every contract · 24h
Funding: +0.0188%; per period · BIN

Aperiodic metrics · BMNR · 24 h

Are takers buying or selling BMNR?

Takers sold $608.1K more than they bought on Binance, OKX and Hyperliquid over 24 h; the heaviest hour, 13:55 UTC, saw $266.9K.

+$329.0K0−$329.0K

00:55 UTCnow

flow.volume_delta_notionalbusiest contract on each venue · hourly · 24 h

What does it cost to cross BMNR's spread?

L1 liquidity

5.61 bps median on Binance USDT, wider than 85% of the 200 most traded perps.

#1BTC0.015 bps
#2ETH0.052 bps
#3SOXL1.57 bps
#5SOL1.25 bps
#10SPCX0.71 bps
#25SP5000.13 bps
#50MUU5.65 bps
#100INTW1.73 bps
#153BMNR5.61 bps
#200MON6.08 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at BMNR's best price?

L1 liquidity

$11.3K at the best bid and ask on Binance USDT, on average, deeper than 76% of the 200 most traded perps.

#1BTC$656.6K
#2ETH$268.9K
#3SOXL$87.6K
#5SOL$157.0K
#10SPCX$17.6K
#25SP500$112.0K
#50MUU$21.1K
#100INTW$1.3K
#153BMNR$11.3K
#200MON$2.3K

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is BMNR's book leaning?

L2 imbalance

Leaned to the bid in 15 of 24 hours on Binance USDT; 51% bids over the day.

54% bid046% bid

00:55 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does BMNR trade?

OHLCV

Binance USDT took 88% of $28.4M traded in 24 h.

volume sharespread

Binance USDT88%5.61
OKX USDT11%5.63
Hyperliquid xyz USDC1.5%17.8

ohlcv.volume_notionaleach contract · 24 h

Does BMNR trade away from its index?

Basis

7.38 bps above its index on Binance USDT now; 0.36 bps below to 17.5 bps above over 24 h.

+17.5 bps0−17.5 bps

00:55 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in BMNR?

Open interest

$12.0M open across 3 contracts: +1.3% in contracts, −5.6% in dollars over 24 h.

$12.7M$11.7M

00:55 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on BMNR?

Funding

Longs pay on 2 of 3 contracts; Binance USDT charges +0.0188% a period (Hyperliquid’s are hourly).

Binance USDT+0.0188%
OKX USDT+0.0000%
Hyperliquid xyz USDC+0.0006%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

BMNR's 3 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Binance USDTperpetual-BMNR-USDT:USDT	17.340	-6.12%	$24.9M	$6.6M	+0.0188%	5.61	Charts →
OKX USDTperpetual-BMNR-USDT:USDT	17.350	-6.06%	$3.0M	$2.9M	+0.0000%	5.63	Charts →
Hyperliquid xyz USDCperpetual-XYZ:BMNR-USDC:USDC	17.394	-5.92%	$413.6K	$2.5M	+0.0006%	17.8	Charts →

History · a year of 5m bars per series · busiest contract on each venue

Every chart for BMNR →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

# aperiodic.io/markets: BMNR on Binance, OKX and Hyperliquid
# 5m bars, 2025-11-13 to 2026-11-13. Install: pip install "aperiodic[polars]"
# Needs an API key (https://aperiodic.io/home/api) on a plan with flow, basis, open_interest, funding (Pro) and l1_liquidity, l2_imbalance (Prime).
# OKX: okx-perps l1_liquidity and l2_liquidity count contracts, not coins (BTC-USDT-SWAP is 0.01 BTC each). Multiply by the contract size to match the page.
API_KEY = os.environ["APERIODIC_API_KEY"]
# timestamp="true" keys bars on capture time, as on the page; "exchange" keys them on exchange time.
PERIOD = dict(
    interval="5m",
    timestamp="true",
    start_date=date(2025, 11, 13),
    end_date=date(2026, 11, 13),
)
CONTRACTS = [
    ("binance-futures", "perpetual-BMNR-USDT:USDT"),
    ("okx-perps", "perpetual-BMNR-USDT:USDT"),
    ("hyperliquid-perps", "perpetual-XYZ:BMNR-USDC:USDC"),
]

frames = {}
for exchange, symbol in CONTRACTS:
    frames["flow", exchange, symbol] = get_metrics(
        api_key=API_KEY,
        metric="flow",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["l1_liquidity", exchange, symbol] = get_metrics(
        api_key=API_KEY,
        metric="l1_liquidity",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["l2_imbalance", exchange, symbol] = get_metrics(
        api_key=API_KEY,
        metric="l2_imbalance",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["basis", exchange, symbol] = get_derivative_metrics(
        api_key=API_KEY,
        metric="basis",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["open_interest", exchange, symbol] = get_derivative_metrics(
        api_key=API_KEY,
        metric="open_interest",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["funding", exchange, symbol] = get_derivative_metrics(
        api_key=API_KEY,
        metric="funding",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )

Every number is from Aperiodic's own 5-minute bars, 15 minutes behind.

Contract

Price

24h

Volume 24h

Open interest

Funding

Spread

Binance USDTperpetual-BMNR-USDT:USDT

17.340

-6.12%

$24.9M

$6.6M

+0.0188%

5.61

Charts →

OKX USDTperpetual-BMNR-USDT:USDT

17.350

-6.06%

$3.0M

$2.9M

+0.0000%

5.63

Charts →

Hyperliquid xyz USDCperpetual-XYZ:BMNR-USDC:USDC

17.394

-5.92%

$413.6K

$2.5M

+0.0006%

17.8

Charts →

import os from datetime import date from aperiodic import get_derivative_metrics, get_metrics # aperiodic.io/markets: BMNR on Binance, OKX and Hyperliquid # 5m bars, 2025-11-13 to 2026-11-13. Install: pip install "aperiodic[polars]" # Needs an API key (https://aperiodic.io/home/api) on a plan with flow, basis, open_interest, funding (Pro) and l1_liquidity, l2_imbalance (Prime). # OKX: okx-perps l1_liquidity and l2_liquidity count contracts, not coins (BTC-USDT-SWAP is 0.01 BTC each). Multiply by the contract size to match the page. API_KEY = os.environ["APERIODIC_API_KEY"] # timestamp="true" keys bars on capture time, as on the page; "exchange" keys them on exchange time. PERIOD = dict( interval="5m", timestamp="true", start_date=date(2025, 11, 13), end_date=date(2026, 11, 13), ) CONTRACTS = [ ("binance-futures", "perpetual-BMNR-USDT:USDT"), ("okx-perps", "perpetual-BMNR-USDT:USDT"), ("hyperliquid-perps", "perpetual-XYZ:BMNR-USDC:USDC"), ] frames = {} for exchange, symbol in CONTRACTS: frames["flow", exchange, symbol] = get_metrics( api_key=API_KEY, metric="flow", exchange=exchange, symbol=symbol, **PERIOD, ) frames["l1_liquidity", exchange, symbol] = get_metrics( api_key=API_KEY, metric="l1_liquidity", exchange=exchange, symbol=symbol, **PERIOD, ) frames["l2_imbalance", exchange, symbol] = get_metrics( api_key=API_KEY, metric="l2_imbalance", exchange=exchange, symbol=symbol, **PERIOD, ) frames["basis", exchange, symbol] = get_derivative_metrics( api_key=API_KEY, metric="basis", exchange=exchange, symbol=symbol, **PERIOD, ) frames["open_interest", exchange, symbol] = get_derivative_metrics( api_key=API_KEY, metric="open_interest", exchange=exchange, symbol=symbol, **PERIOD, ) frames["funding", exchange, symbol] = get_derivative_metrics( api_key=API_KEY, metric="funding", exchange=exchange, symbol=symbol, **PERIOD, )