Curve Finance has launched Llamalend v2 on the Optimism network, marking a significant upgrade to its isolated lending protocol. This new version has received a grant of 250,000 OP tokens from Optimism to encourage liquidity and attract users to the platform.
What enhancements do we see in Llamalend v2?
Unlike its predecessor, which was primarily tied to the crvUSD stablecoin, Llamalend v2 supports a variety of collateral and borrowing assets. Now, users can engage with LP tokens, which are given in exchange for providing liquidity in decentralized finance (DeFi) pools, alongside PT tokens that represent fixed-yield investments that emerged through protocols like Pendle.
One of the crucial changes in this version is the introduction of soft liquidations, replacing the conventional hard liquidation model. In a hard liquidation scenario, collateral is sold immediately when it dips below a certain value, often resulting in losses. In contrast, soft liquidations represent a more strategic approach, where the system gradually adjusts collateral by converting it into the borrowed asset as prices decrease, and it reverts back to collateral once prices improve.
Who oversees risk management for Llamalend?
LlamaRisk, a firm specializing in DeFi risk management and a partner in Curve governance since 2021, now acts as the market curator for Llamalend. This firm plays a vital role in setting risk parameters, determining how much users can borrow based on their collateral types, outlining interest rate curves, and calibrating liquidation thresholds to ensure a stable and efficient lending environment.
Why partner with Optimism at this time?
The 250,000 OP token grant from Optimism is a strategic financial asset aimed at fostering growth within the protocol. The initial deployment starts with a test phase set for Q2 2026, allowing Curve to rigorously test the new asset types and the soft liquidation process before considering expansion to additional blockchain platforms. This approach ensures a thorough evaluation of the system's functionality and robustness.