In Development

Built for
Hyperliquid.

HyperLLM is trained on what generic models ignore: funding rates, liquidation math, fee tiers, and the execution mechanics that determine what a trade actually costs.

Start Trading

HyperLLM is built by UV Labs. It is an independent product and is not affiliated with or endorsed by Hyperliquid.

Platform Mechanics

What it knows.

Funding Rates

Funding can exceed 200% APR on crowded trades. The model tracks real-time rates, flags expensive holds, and factors funding into entry/exit timing.

Liquidation Math

Computes exact liquidation prices for cross and isolated margin. Accounts for unrealized PnL, open orders, and position adjustments, and models ADL exposure so the risk is visible in every decision.

Fee Optimization

Taker fees are 3x maker fees (0.045% vs 0.015%, as of mid-2026). The model picks order types to minimize costs: when ALO makes sense for rebates, when paying taker is worth it.

Queue Priority

Cancels process before fills. Liquidity disappears when you need it most. The model understands FIFO queue dynamics and when cancel/replace costs you your spot.

Exit Execution

Stop-market orders slip badly in thin books. The model structures TP/SL correctly: trigger distances, limit vs market, partial exits to avoid walking the book.

API Integration

Correct endpoint selection, proper rate limiting, WebSocket subscriptions. Handles the nuances of HL's API that trip up most trading bots.

HLP Vault Dynamics

HLP takes the other side when the book is thin. The model understands when the vault is your counterparty, how liquidations flow into HLP, and what that means for fills.

Cross-Margin Portfolio

Unrealized PnL on one position affects margin for others. The model tracks portfolio-level risk: how a winner funds a loser, when correlation kills you, total liquidation price.

HIP-3 Markets

Works on any perps built on Hyperliquid. Native markets, Trade.xyz, and future HIP-3 deployments all share the same mechanics. One model, every venue.

Mechanics are the silent tax.

Funding, fees, fills, and liquidations are deterministic. HyperLLM models them so your agent's decisions account for them. It is trained on UV's decision-episode corpus — three years of live trading data on perp-DEX mechanics.