BullpenFi vs Hyprearn

Name: BullpenFi vs Hyprearn OpenChainBench measurements
Creator: OpenChainBench
License: https://creativecommons.org/licenses/by/4.0/

BullpenFi leads on the only live benchmark. BullpenFi wins on Hyperliquid frontends builder revenue leaderboard ($3,139 vs $25.64).

Read methodology Last measured Sat, 22 Aug 2026 02:13:05 UTCWindow: rolling 24h1 shared benchmark

BullpenFi

Non custodial multi platform trading terminal unifying Hyperliquid perps, Polymarket prediction markets, and Solana spot in one app.

Hyprearn

HyprEarn is an AI assistant for Hyperliquid perps that generates one click trade setups across HL pairs and HIP 3 markets, executed via a registered builder code.

Side by side measurements

Hyperliquid frontends builder revenue leaderboard

Trading

Provider	Builder fees collected	Volume routed	Users 24h	Effective fee bps	Time since last fill
BullpenFi	$3,139	$10.91M	129	0.029%	35.9 s
Hyprearn	$25.64	$57.3K	14	0.045%	9.2 min

Ranking is by raw builder fee revenue in USD, not by value for users. Bigger number means more fees collected via the on-chain builder code field. For the trader cost perspective, switch to the Effective fee bps companion tab. Native Hyperliquid UI orders carry no builder code and are excluded. Data from a local hl node tailing every fill on mainnet.

Frequently asked questions

BullpenFi vs Hyprearn: which one is better?

BullpenFi and Hyprearn are compared on 1 shared OpenChainBench benchmarks. BullpenFi leads on Hyperliquid frontends builder revenue leaderboard. See the live table on this page for every metric.

Which is cheaper, BullpenFi or Hyprearn?

On the Hyperliquid frontends builder revenue leaderboard benchmark, BullpenFi leads at $3,139 versus Hyprearn at $25.64. Live measurement is updated continuously by the OpenChainBench harness.

How is the BullpenFi vs Hyprearn comparison measured?

Every benchmark on this page uses the same open methodology, published at https://openchainbench.com/methodology. Data is CC-BY-4.0. Measurement harnesses are MIT-licensed.

How this pair was selected

Auto-generated pairs require: both providers in the same benchmark for seven consecutive days, at least 1000 samples per provider, observable third-party search demand, and a public /products/[slug] page on OCB. Editorially curated pairs (like this one) may publish early when search demand is high and data is accruing — panels with fewer than 100 samples are shown as provisional. The full pair ledger is versioned in the public repo.