Why 1,400 Builder Codes Split Scraps While 15 Earn Millions

Hyperliquid's builder code program has distributed over $90.7 million in revenue to developers. That number sounds like a rising tide lifting all boats. It isn't. Fifteen builder codes captured roughly $74.6 million of that total. The other 1,396 codes split the remaining $16 million between them.

Figures as of July 2026, from HyperTracker's builder leaderboard.

The power law isn't surprising if you've watched any platform economy mature, but the shape of it reveals something useful. Revenue per user across the top 15 ranges from $69 to $1,395. That's a 20x gap between builders on the same protocol, charging similar fee rates, accessing the same liquidity. The difference is strategy, and this article breaks down the three archetypes that actually generate meaningful builder code revenue on Hyperliquid.

The Concentration Is Extreme

Before we examine why some builders win, look at just how steep the drop-off is. Phantom sits at the top with $23.6 million in all-time builder code revenue. Based follows at $15.2 million. Together, those two codes account for nearly 43% of all builder revenue ever generated on Hyperliquid.

By rank five (Insilico at $3.7 million), the per-code revenue has already dropped by 84% from the leader. By rank 15 (Minara AI at $775K), you're looking at a 97% decline from Phantom's total. Everything below rank 15 lives in a long tail where most codes earn modest amounts or nearly nothing.

This isn't a criticism of the program. It's exactly what you'd expect from any permissionless fee-sharing model. The barrier to entry is 100 USDC in a Hyperliquid perps account and a working integration. Low barriers produce lots of entrants. Lots of entrants produce power law distributions. What matters for a prospective builder isn't the average payout. It's understanding which strategies actually break through.

Archetype 1: The Distribution Giants

Phantom, MetaMask, and Rabby are all wallet providers. Their builder code revenue comes from embedding Hyperliquid perps trading into products that already have millions of active users. When someone trades through Phantom's in-wallet Hyperliquid interface, every fill gets tagged with Phantom's builder code. No separate sign-up. No new app to install. Just a feature inside the wallet people are already using.

The numbers bear this out. Phantom has 153,128 users attributed to its builder code and generates $23.6 million in revenue. MetaMask has 52,534 users and $8.1 million. Rabby: 19,031 users and $1.5 million. The pattern is consistent: revenue scales linearly with user count because each user generates a moderate volume of trades.

Revenue per user in this archetype tends to fall between $77 and $154. That's not high compared to other archetypes, but the sheer scale of the user base makes up for it. Phantom's $154 per user times 153,000 users produces the largest builder code revenue on the platform.

The moat here is obvious. You need an existing product with real distribution before you integrate Hyperliquid. Building a wallet from scratch specifically to earn builder fees is not the play. The distribution giants are the ones who already owned the user relationship and added perps as a feature.

Archetype 2: The Volume Machines

Insilico, Mass, and TreadFi represent the opposite model. Their user counts are small: 3,339 for Insilico, 1,054 for Mass, and 4,835 for TreadFi. These aren't mass-market consumer products. They're execution tools built for traders who size large and trade frequently.

The revenue-per-user numbers tell the story. Mass generates $1,395 per user. Insilico: $1,113 per user. TreadFi: $463 per user. Compare that to Phantom's $154 per user, and you see why fewer users can still produce millions in revenue. Each user contributes dramatically more trading volume.

Insilico pushed $36.3 billion in all-time volume from 3,339 users, which puts its average volume per user above $10.8 million. That kind of per-user volume only comes from quant desks, market makers, and algorithmic strategies that execute thousands of trades per account. The product needs to be built for that audience: fast execution, advanced order types, API-first interfaces that integrate with automated trading systems.

For builders considering this path: you don't need 100,000 users. You need 1,000 of the right users. The challenge is building a product compelling enough that professional traders will route their flow through your frontend instead of connecting directly to Hyperliquid's native interface or writing their own execution layer.

Archetype 3: The Aggregators and Social Platforms

Based, Axiom, and Dreamcash occupy the middle ground. They aren't wallets with massive installed bases, and they aren't execution tools for quants. They aggregate demand through copy trading, DEX aggregation, or social trading features that give users a reason to trade through a third-party frontend.

Based is the standout in this category: 42,967 users generating $44.9 billion in volume and $15.2 million in revenue. That's $354 per user, which sits between the wallet model and the quant model. Axiom brings a similar user count (34,093) but earns $69 per user, suggesting its users trade less aggressively or the product captures a smaller share of their total activity.

The key variable in this archetype is retention. Copy-trade and aggregation platforms need users to keep coming back, because builder codes only generate revenue when trades execute. A user who signs up, mirrors a few positions, and then stops is worth very little. A user who makes your platform their default trading interface? That's a recurring revenue relationship.

For builders exploring this model, the competitive question is clear: why would a trader use your platform instead of going directly to Hyperliquid? Copy trading, better analytics, social features, automated strategies, and curated trade signals are all valid answers. But each one requires building and maintaining a product layer that's genuinely better than what the user can get on their own.

What the Archetypes Mean for New Builders

If you're evaluating whether to build on Hyperliquid's builder code program, the leaderboard data suggests a few practical filters.

Do you already have users? If you operate a wallet, a DeFi dashboard, or any product with a meaningful installed base, the distribution giant model is your fastest path to builder revenue. The integration work is relatively straightforward, and every existing user who discovers Hyperliquid perps through your interface becomes a revenue source.

Can you attract professional traders? If you're building execution infrastructure, the volume machine model lets you earn significant revenue from a small user base. But the product bar is high. Quants and market makers have specific requirements around latency, order types, and API reliability. Meeting those requirements well enough to capture their flow is the hard part.

Can you solve a distribution problem Hyperliquid can't? If you can bring new user segments to Hyperliquid through copy trading, social trading, or aggregation, the third model offers a path. The moat is product quality and user experience, because aggregation platforms compete with each other for the same pool of traders.

The fee caps matter less than you think. Hyperliquid allows up to 10 basis points (0.10%) on perps and up to 100 basis points (1.00%) on spot. Most builders charge well below the cap. The variance in revenue per user comes from volume differences, meaning how much and how often each user trades, rather than fee rate optimization. A builder charging half the fee rate with twice the per-user volume earns the same revenue.

Tracking Builder Economics with Our API

Static leaderboard snapshots show you who's winning today. They don't tell you who's gaining momentum, which codes attract specific trader types, or whether a builder's revenue is accelerating or decaying. Programmatic access changes that.

Our /builders/list endpoint lets you pull the full builder leaderboard filtered by timeframe: daily, weekly, monthly, or all-time. That means you can compute growth rates, compare momentum across codes, and spot new entrants before they show up on anyone's radar. A quick example:

curl -X GET \
  "https://ht-api.coinmarketman.com/api/external/builders/list/timeframe/week" \
  -H "Authorization: Bearer YOUR_TOKEN"

The response includes revenue, volume, and user count per builder for that period. Compare consecutive weekly pulls and you have a momentum tracker for the entire ecosystem.

Where it gets more interesting is combining builder data with our cohort analytics. Every wallet on Hyperliquid is classified into one of 16 behavioral cohorts: eight by wallet size (Shrimp through Leviathan) and eight by all-time PnL (Money Printer through Giga-Rekt). When you cross-reference builder code users against cohort data, you can answer questions that no public dashboard surfaces. Which builder codes attract the most Money Printer wallets? Is a code's volume driven by a handful of Leviathans or by thousands of Fish-tier traders? Are the Giga-Rekt wallets churning through one specific platform?

That kind of segmentation turns a static ranking into a strategic tool, whether you're evaluating a competitor's builder code, choosing which builders to partner with, or tracking your own code's user composition over time.

Monitor Builder Code Performance Programmatically

Query the full builder leaderboard by timeframe. Track revenue, volume, and user trends for any code. Cross-reference with 16 behavioral cohorts for deeper segmentation.

Explore HyperTracker API

The Power Law Will Get Steeper

Three trends will concentrate builder revenue further as the ecosystem matures.

HIP-3 asset expansion adds traditional assets (equities, commodities, forex) to Hyperliquid's perps market. The builders who already have distribution will be first to offer these markets through their interfaces, which compounds their volume advantage. A wallet that routes equity perps trades through its builder code taps a market far larger than crypto-native perps alone.

HIP-4 prediction markets create a new category of builder revenue. Deployers earn a share of the trading fees their markets generate, and every trade on a prediction market frontend can also carry a builder code. The builders who move first to integrate prediction markets alongside perps will capture this incremental volume.

Institutional integrations shift the volume mix toward larger trade sizes. As more custody solutions, prime brokerage layers, and enterprise wallets come online, the average trade routed through builder codes will grow. That benefits the distribution giants and volume machines disproportionately, because institutional flow tends to concentrate through a small number of trusted frontends.

The 1,411-code ecosystem will keep growing. But the revenue will keep concentrating. That's the pattern of every platform economy: permissionless entry, power law outcomes. If you're building on Hyperliquid today, the question isn't whether builder codes work. They clearly do. The question is which of the three archetypes fits your product, your users, and your distribution advantage. Pick the wrong model and you join 1,396 codes splitting $16 million. Pick the right one, execute well, and the leaderboard has room.