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- Manual borrowing is now live directly on HyperCore.
- HYPE and BTC have different collateral requirements.
- Stablecoin rates respond dynamically to utilization.
- HYPE-backed debt introduces a new market feedback loop.
Hyperliquid has launched manual borrowing on HyperCore, allowing users to borrow USDC and USDT against HYPE and Bitcoin while bringing lending, collateral management and trading onto the same underlying infrastructure.
Manual borrows are live on Hyperliquid
Portfolio margin and manual borrows use the same underlying HyperCore infrastructure, with $269M in assets borrowed today.Users can supply HYPE and BTC as collateral to borrow quote assets (USDC and USDT). Borrowed quote assets pay… pic.twitter.com/C3crESxaM0
— Hyperliquid (@HyperliquidX) September 18, 2026
The feature went live with $269 million in assets borrowed on September 18, according to Hyperliquid. More important than the initial volume is what happens next: borrowing introduces a direct link between HYPE’s market price, stablecoin liquidity and liquidation activity inside HyperCore.
How Borrowing on Hyperliquid Works
According to Hyperliquid’s technical documentation, manual borrowing is available for Manual/Standard and Unified Accounts, while Portfolio Margin accounts use automated borrowing and therefore do not offer the same manual borrow action.
Users can supply HYPE or BTC as collateral and borrow quote assets, currently USDC and USDT. Borrowed balances accrue interest, while users supplying quote assets earn interest.
Hyperliquid’s official Manual Borrows documentation
The system separates collateral from yield-generating supply. HYPE and BTC deposited as collateral do not earn interest, while supplying USDC or USDT can generate interest but does not increase a user’s manual borrowing capacity.
For traders looking for how to borrow on Hyperliquid, the process effectively converts an existing HYPE or BTC position into borrowing capacity without requiring the underlying collateral to be sold.
That creates additional capital flexibility, but the amount available depends heavily on which asset is deposited.
Hyperliquid LTV Ratios Put HYPE and BTC on Different Terms
The two collateral assets receive materially different risk parameters.
A trader depositing $10,000 of HYPE could therefore have up to $6,500 of initial borrowing capacity under the stated LTV, compared with $5,000 against the same value of BTC, before accounting for other applicable limits.
The gap reflects how HyperCore assigns different collateral parameters to individual assets rather than treating every dollar of collateral equally.
Interest Rates Are Controlled by Utilization
Hyperliquid does not offer borrowers a permanently fixed interest rate.
Borrowing costs change according to utilization, or how much available USDC and USDT liquidity is currently being borrowed. The interest index updates hourly, meaning borrowing costs can change as demand for stablecoin liquidity rises or falls.
Suppliers of USDC and USDT receive the interest generated by borrowers, minus the portion retained by the protocol.
Hyperliquid’s documentation says 10% of borrowed interest is directed to a reserve intended to cover potential future liquidation losses. The remaining interest flows to suppliers.
This creates an important distinction between borrow APY and supply APY. Even before accounting for the protocol’s reserve, not every dollar deposited into a supply pool is necessarily being borrowed.
For users evaluating the lending market, the headline supply rate therefore matters less without its accompanying utilization rate.
A high APY supported by persistently high utilization describes a very different lending market from a temporary rate spike caused by a short burst of borrowing demand.
HYPE Collateral Creates a New Liquidation Feedback Loop
The most consequential change is not simply that traders can borrow stablecoins. It is that HYPE can now support debt inside the same ecosystem where it trades.
Consider a user borrowing against HYPE near the permitted initial LTV.
If HYPE falls sharply while the USDC or USDT debt remains outstanding, the collateral value declines but the liability does not. Accrued interest can push the ratio further toward the liquidation threshold.
For HYPE, partial liquidation begins at an 82.5% LTV, compared with 75% for BTC.
This creates a potential feedback channel. A decline in HYPE can weaken collateral positions, increasing liquidation pressure. Liquidations can then alter collateral inventories and market exposure during the same period of volatility.
The magnitude of that risk depends on information the launch-day borrowing total cannot reveal on its own.
What matters is collateral composition.
A lending market dominated by BTC collateral would have a different relationship with Hyperliquid’s native token than one where a large share of stablecoin debt is secured by HYPE.
Hyperliquid Is Pulling More of the Trader Balance Sheet Into HyperCore
Manual borrowing also changes what traders need to leave Hyperliquid to accomplish.
A HYPE holder who wants stablecoin liquidity no longer necessarily needs to sell the token or move it to an external lending protocol. The user can retain the collateral position, borrow quote assets and deploy that liquidity elsewhere.
Trading, collateral valuation, credit and liquidation can therefore increasingly interact through HyperCore.
That gives Hyperliquid another way to keep capital within its ecosystem, but it also makes the health of its credit market more relevant to traders who may never think of the platform primarily as a lending protocol.
The $269 million launch-day borrowing figure establishes initial demand. It should not be the main metric used to judge what happens next.
Utilization rates, borrow APYs, the HYPE-to-BTC collateral mix and the amount of debt approaching liquidation thresholds will provide a clearer picture of whether manual borrowing develops into a durable credit market.
Those metrics will also answer the bigger question created by the launch: how much leverage can Hyperliquid build around HYPE before the lending market itself begins influencing the token’s behavior during periods of volatility?
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