Hyperliquid HIP-3 deployer revenue leaderboard
How much USD deployer fee revenue each HIP-3 builder-deployed dex collected over the rolling 24h, 7 day and 30 day windows. Data from a local hl node tailing every fill on mainnet.
Read this carefully
Ranking is by raw deployer fee revenue in USD, not by value for traders. Bigger number means more fees collected via the on chain deployerFee field on the dex's namespaced markets. For the trader cost perspective, switch to the Effective fee bps companion tab. Core Hyperliquid markets (no namespace) carry no deployer fee and are excluded. Some dex namespaces are not yet matched to a public brand; they are listed under their on chain namespace until identified.
This page answers one question. Which HIP-3 builder-deployed dex on Hyperliquid collected the most deployer fee revenue in USD over the last 24 hours, 7 days and 30 days. HIP-3 lets any team that stakes 500,000 HYPE deploy its own perpetual markets on HyperCore under a dedicated namespace (xyz:AAPL, vntl:MAG7, km:US500), set the fee policy for those markets, and collect a deployer cut on every fill. The mechanism powers the tokenized stock, index and commodity perps wave on Hyperliquid: trade.xyz alone routinely clears several billion dollars of daily notional across more than 70 equity and commodity markets. The bench ranks every namespace observed on mainnet by the dollar amount its deployer collected through the on chain deployerFee field, alongside routed volume, unique trader counts and the number of live markets. Data comes from a local hl node operated on OCB infrastructure tailing the Hyperliquid mainnet fill stream; a Go harness aggregates per dex over rolling windows and exposes Prometheus gauges that this page consumes. End to end staleness from fill landing on chain to page render is typically under one minute.
Methodology
The bench ranks HIP-3 builder-deployed dexes by the USD value of deployer fees they collected over rolling 24 hour, 7 day and 30 day windows. Source data is a local hl node operated on OCB infrastructure that writes every block of fills to disk as one JSON line. A Go harness tails these files, attributes each fill carrying a namespaced coin (xyz:AAPL belongs to the xyz dex) and a deployerFee value, and increments per dex hourly buckets keyed by the UTC hour floor of the fill timestamp. At publish time the harness sums the recent 24, 168 and 720 hourly buckets and exposes the totals as Prometheus gauges (hl_hip3_deployer_fees_usd_24h, _7d, _30d), plus routed volume, unique trader counts from per day wallet sets, live market counts and an effective fee rate in basis points. The dex set is discovered dynamically from the fill stream, no registry needed, because HIP-3 namespaces are unique on chain by construction. The bench does not place trades, does not touch private keys, and does not depend on any internal Mobula service.
Frequently asked
What does this benchmark measure?
The USD value of deployer fees each HIP-3 builder-deployed dex collected over rolling 24 hour, 7 day and 30 day windows. HIP-3 lets a team that stakes 500,000 HYPE deploy its own perpetual markets on Hyperliquid under a dedicated namespace and collect a fee cut on every fill. The bench sums every fill's deployerFee value per namespace and publishes the total per timeframe.
What is HIP-3?
Hyperliquid Improvement Proposal 3, builder-deployed perpetuals. It opens HyperCore market deployment to outside teams: stake 500,000 HYPE, deploy markets under your namespace, set the fee policy, collect the deployer cut. It powers the tokenized stock, index and commodity perps on Hyperliquid, which represent a large share of platform volume.
Where does the data come from?
A local hl node operated on OCB infrastructure tails the Hyperliquid mainnet. The node writes every block of fills to disk; a Go harness running on the same host reads these files continuously, attributes namespaced fills to their dex, and aggregates per hour. No third party API, no internal Mobula service.
How are dexes identified?
By their on chain coin namespace. Every HIP-3 market trades under a prefix (xyz:AAPL, vntl:MAG7, km:US500) that is unique to its deployer. The set is discovered dynamically from the fill stream, so a brand new deployer appears on the leaderboard with its first fill. Namespaces not yet matched to a public brand are listed under the raw prefix.
Why is trade.xyz so far ahead?
It operates the deepest tokenized equity and commodity catalog on Hyperliquid, more than 70 markets including the large cap US names, and captures the bulk of HIP-3 open interest. Deployer revenue is volume times fee policy, and xyz leads on both breadth and notional.
What does the Effective fee bps column tell me?
Deployer fees divided by notional volume, in basis points. It is the trader perspective: what a representative dollar of flow paid the dex operator. Two dexes with the same revenue can have very different fee rates if one routes ten times the volume.
Why do 30 day figures look low for some dexes?
The node keeps hourly fill files for a bounded horizon and the harness backfills what exists on disk. Until 30 full days of history accumulate behind a dex, its 30d figure covers the available horizon and grows toward the full window. The 24h and 7d views are complete.
How often does the page refresh?
Every 30 seconds at the harness and scrape level. The page itself uses incremental static regeneration with a 60 second window, so headline values are at most 90 seconds stale plus chain propagation delay.
Can I cite a value from this page?
Yes. Every number is a Prometheus query exposed via the OCB API endpoints. The harness source is open at the link in the source field below. Cite the value and the timestamp at the top of the page.
Source code github.com/ChainBench/OpenChainBench/tree/main/harnesses/hyperliquid-frontends