Cicada Capital

By Max Moris, CEO and Аounder of Cicada - a Dubai-based Market Making company with 6 years of personal experience, 1,000+ projects, and 500+ exchange listings.
• Watch on YouTube: https://youtu.be/KjoDUuXwQ_g
Last year, a founder signed a contract for free market making services. Four months later, the project had lost six million dollars. The market maker had made six million dollars. And hadn't violated a single line of the agreement. Everything was in the contract. Nobody read it.
This is the story of the three contract models that exist in this industry, what they actually cost, and why "free" is the most expensive word in crypto market making.
Three MM Models - Different Rules
Every market making contract falls into one of three categories. Retainer: you pay a fixed monthly fee. Loan: you give the market maker your tokens. And "free": which is how loans get sold to founders who don't understand what they're signing.
Retainer: Clean and Honest
The retainer model is the simplest. The project pays a fixed monthly fee. The market maker operates on your exchange accounts via API keys, with no ability to deposit or withdraw funds. You keep full control of your money. All profit generated from volatility goes to you, not to the market maker. They receive only what's written in the invoice.
This is the only model in the industry where incentives are completely transparent. We get paid for the work. We do the work.
At Cicada, services start at $3,500 per month, ranging up to $8,000 depending on the number of exchanges. Pay several months upfront and you get a discount.
What that fee covers:
A professional trading team and 24/7 support.Dozens of algorithms running simultaneously on your token, built on C++ infrastructure with fast updates for every exchange.An online dashboard with full real-time statistics. Every trade, every order, every metric, visible at any moment.Risk control and weekly reports.
There's also something I offer clients inside the retainer that's entirely voluntary and not written into the contract. For clients who want it, we open a separate account holding only the project's tokens.
Our job is to work that account so that by the end of month, the token balance is unchanged and there's an additional $USDT position on top. We don't touch your token holdings, but through volatility work, we generate a dollar-denominated gain.
If there's a positive result at month end, the client can choose to share part of it with us. If there's no result, no claims - we keep working the following month.
For most projects, especially at listing, retainer is the only real option. If your market cap is under $100 million, it's retainer. No exceptions. The loan model will explain why.
Loan: The Trojan Horse
The loan model looks attractive on paper. The project lends tokens to the market maker, sometimes with stablecoin added. The MM uses those tokens as liquidity in the order book. No monthly invoice. No payment schedule. The launch chart looks clean. Everyone seems happy.
Here's the math on what actually happens:
Take a hypothetical project. FDV of $50 million. Token price at TGE: $1.00. You lend the market maker 5% of the supply - 2.5 million tokens, worth $2.5 million.Listing day comes with hype. Price rises to $3.00. The market maker sells your tokens, the ones you lent them - at an average of $3.00. They now hold $7.5 million in cash.Three to six months pass. Unlocks start. The marketing budget runs dry. Hype fades. Price drops to $0.50.The entire time, the market maker has been trading. Not sitting on cash - actively profiting from every move up and down. Each swing in price is potential revenue for them, not for you.Then comes the final move. The market maker buys back those 2.5 million tokens at $0.50. Spends $1.25 million. Returns the tokens to your project per contract. Terms fulfilled. Signature valid.
Net profit for the market maker: $6.25 million on the price difference alone, plus everything earned on volatility across those months. What the project has: a collapsed chart, a damaged reputation, and the same 2.5 million tokens that are now worth a fraction of what they were.
And the market maker didn't break the contract. They did exactly what you agreed to. You handed them your tokens and said "trade." They traded. In their favor. Every day. On every move.
This is the most common reason founders come to us after leaving another market maker. Every one of them thought their situation was different.
Free: There's No Such Thing
When someone tells you their services are free, translate it as: "We'll make our money another way, and we won't be telling you how."
Free market makers don't exist. If no invoice is coming your way, that doesn't mean you're not paying. It means you're paying in tokens, in price control, in community trust, and eventually in the project itself.
When Loan Actually Works
The loan structure isn't inherently bad. It's a tool. The question is who's holding it and under what conditions. Loan works when your market cap is above $100 million. At that capitalization, no single loan can meaningfully manipulate the price - the math doesn't allow it.
It works for smaller exchanges you don't want to actively manage. Send a loan and let it run. It's required on certain exchanges. Coinbase is the most prominent example. Without a loan structure, you can't list there.
And for large projects, it creates something powerful: you can split the loan across multiple market makers who then compete with each other. Liquidity multiplies. Spreads tighten. Users trading your token benefit directly.
The question isn't "is loan good or bad." The question is where you are and what you're trying to accomplish.
Three Questions to Ask Before Signing:
What happens to my tokens if the market maker sells them and the price drops?
If the answer is "we'll buy back at market" - you already know how this ends.How quickly can I exit the contract if something goes wrong?
If the answer is "not for two years" - that's a red flag.Do our incentives actually align?
If the market maker can profit when your project is doing badly - something went wrong before the contract was even signed.
Good contracts survive these questions. Bad ones fall apart on the first one. Read the contract before you sign it, not after the chart collapses and the treasury is empty.
Your MM Should Win When You Win
Retainer is the right structure for most projects, especially at listing. You pay clearly and you sleep at night. Volatility profit is yours. Control is yours, the market maker receives only what's in the invoice.
Loan is a functional tool, but in this model, volatility profit goes to the market maker, not to you. That's fine at the right capitalization, for the right exchanges, when you're running competition between multiple providers.
One more thing worth understanding. Your market maker needs to make money too. This isn't charity. It's a business. A market maker that doesn't earn doesn't survive, doesn't invest in technology, doesn't keep a strong team. And ultimately, you lose.
So sometimes a loan is a good model. You solve your problems. The market maker earns. Both sides win.
The question isn't whether your market maker should make money. They should. The question is balance. If your market maker makes six million and you lose six million - that's extraction. If your market maker profits from the project growing alongside you - that's the relationship you want.
"Free" doesn't exist. If there's no invoice in the contract, there's something else in there. Read it. Find it. Run the numbers.
I'm Maxim Moris, Founder of Cicada Market Making. If you need help reviewing a contract before you sign - reach out. I personally review every incoming request together with the team.
Do You Need a Market Maker?

Based on Cicada Market Making Research. All figures sourced from publicly available data including on-chain analytics, platform documentation, academic research, and industry reporting. Featuring insights from Outcome.
In January 2024, total monthly volume across all prediction market platforms sat at roughly $100M. By April 2026, that number reached $24.2B. A 130x expansion in 24 months, with the trajectory showing no signs of flattening. Most people still think of prediction markets as a crypto-native experiment, and that framing is about two years out of date.
Kalshi won its legal battle against the CFTC in May 2025, establishing binary event contracts as legally tradeable instruments under US commodity law.
CME Group entered the category. DraftKings and FanDuel brought their combined 12M+ user base along. Robinhood integrated Kalshi directly into its brokerage interface and generated $300M ARR faster than any product in the company’s history. ICE invested $2B into Polymarket at a $15B valuation, and Kalshi itself reached a $22B valuation in March 2026.
A forming asset class with regulated infrastructure, institutional capital, and mainstream distribution all arriving simultaneously. That convergence is rare and the window it creates for early operators is finite.
Who Actually Makes Money Here
The profit structure of prediction markets is the most important fact about them for anyone considering market-making as a strategy.
Across Polymarket's 1.6M registered accounts, 0.1% of wallets capture 67% of all profits. That top cohort, roughly 2,000 addresses, has accumulated approximately $500M since late 2022. On Kalshi, 2.9 losing accounts exist for every profitable one.
Retail participants lose systematically and persistently. They trade on opinion, overweight recent events, and have no access to the pricing models that determine fair value on these instruments.
The professional layer is extraordinarily thin. TRM Labs data shows that accounts with more than 10,000 fills generate 35.2% of total volume. On most Polymarket markets, there are literally one or two active bots providing two-sided liquidity.
The counterparty pool is deep, the competition is minimal, and the behavioral patterns of retail flow are predictable enough to build a durable edge against.
The information asymmetry is large, the professional population is small, and the platforms are actively paying operators to provide liquidity through rebate programs distributing approximately $5M per month. For a market-maker, the structural setup here is about as clean as it gets.
The Platform Landscape
Polymarket and Kalshi together account for 97.5% of all volume. The remaining 17+ platforms share approximately $1.25B annually.That concentration means any serious operation must be native to both dominant venues, while the long tail represents early-entry opportunities where designated market-maker arrangements, equity stakes, and fee-share structures are still negotiable.
Polymarket operates as a decentralized CLOB on Polygon with zero maker fees and a rewards program calibrated to reward tight two-sided quoting.
Kalshi is the regulated counterpart, a CFTC-licensed Designated Contract Market settling in USD with 4% APY on idle balances and 40% of volume already coming from institutional participants.
Three emerging platforms carry strategic weight beyond their current size:
Opinion launched on BNB Chain in October 2025 and generated $3.1B in cumulative volume within three weeks, briefly surpassing both dominant platforms on weekly flow.Limitless on Base runs 30-minute crypto price contracts, a segment that sits closer to short-dated options than traditional prediction markets.Hyperliquid HIP-4, announced in February 2026, brings outcome tokens to Hyperliquid’s L1 unified with the same account infrastructure handling spot and perpetual trading. HIP-3, permissionless perpetuals launched October 2025, now generates 35%+ of Hyperliquid’s total volume, and that precedent defines what early market-maker positioning on HIP-4 at the testnet stage could be worth.
Each of these platforms represents a different entry dynamic, and collectively they suggest that the prediction market landscape is still early enough in its maturation that first-mover advantages across multiple venues remain genuinely available.
The Monetization Stack
The near-term cash flow engine is core market-making on Polymarket’s CLOB. Two-sided quoting across 30–50 markets, calibrated to the rewards formula and optimized for spread capture, generates approximately 50% APR on $500K of deployed capital in conservative modeling. Capital requirement to enter is $50K, and breakeven arrives in 4–6 weeks.
Cross-platform arbitrage between Polymarket, Kalshi, and Opinion Trade layers directly on top of that foundation. IMDEA Networks documented over $40M in extractable arbitrage profit from Polymarket alone across a single 12-month period, analyzing 86M trades.
The opportunity takes three principal forms:
Intra-market arbitrage where YES plus NO prices sum below $1.00 after fees, a structurally risk-free tradeCross-platform pricing gaps on identical events quoted differently across venuesStale-price windows of 30–120 seconds following macro data releases, when Polymarket typically reprices before Kalshi
The crypto-edge layer is where existing options and perpetuals expertise transfers most directly. Polymarket’s 5-minute and 15-minute crypto price markets, launched March 2026, price at systematic discounts to the implied probabilities derivable from Deribit IV.
An operator continuously computing fair value from risk-neutral density and quoting against that model creates an edge that retail participants fundamentally cannot replicate, with directional exposure hedging cleanly through offsetting spot or perpetual positions.
As capital accumulates, the strategy stack expands upward. An OTC desk serving institutional clients who need 100K+ tickets generates 80–200 bps per trade on $5M of working capital.
Delta-neutral holding positions earn 4% APY from both Polymarket and Kalshi simultaneously on long-dated markets. Designated market-maker arrangements on emerging platforms, particularly Hyperliquid HIP-4 pre-mainnet, layer equity upside on top of operating revenue.
Where the Real Margin Lives
The highest-multiple opportunity in this landscape sits at the intersection of prediction market liquidity and institutional capital demand. Family offices, macro hedge funds, and private banks want exposure to political and macroeconomic event outcomes.
The liquidity to express that exposure now exists on regulated platforms at scale. What these institutions lack is an access format compatible with their operating model, meaning USD wire settlement, standard subscription documentation, independent NAV administration, and legal structure that compliance teams can approve.
The gap is operational and legal, and an operator who closes it captures 200–500 bps of structural margin on AUM, with marginal costs approaching zero once the infrastructure is running.
The product architecture runs through an offshore SPV that issues notes to investors, with the portfolio manager deploying capital through qualified custody into Polymarket and Kalshi positions, optionally hedged through Deribit options or treasury bills for principal protection structures. Four products are immediately buildable within this framework:
US Macro Bundle: quarterly rolling basket of 30–40 positions across FOMC decisions, CPI prints, NFP releases, and GDP advances, targeting $10M — $30M in AUM with fee structures generating ~$800K/year at $20MElection Year Hedge: 92% of NAV in T-bills guaranteeing principal return, 8% in delta-neutral position across US midterm and European election outcomes, targeting $20M — $50M in AUM with ~$1.5M — $2M/year in fees at $30MCrypto Catalyst Notes: 100% active exposure across BTC ETF flows, ETH staking yields, halving metrics, and regulatory decisions with Deribit overlay for delta hedging, targeting $5M — $15M in AUMStable Politics Yield: fully deployed across 200+ low-volatility markets with no single position above 1% of NAV, targeting 8–12% net APR to the investor as a stablecoin treasury alternative
Setup cost for the full product infrastructure runs $150K to $250K one-time, with annual operating costs of $300K — . The economics become compelling above $30M in AUM, which is the threshold at which the product layer should activate. Below that, market-making and capital strategies provide the cash flow and track record needed to attract institutional allocators.
The Competitive Clock
The firms that will eventually dominate prediction markets at institutional scale, Susquehanna, DRW, Jump, are watching and some are already building. What they have not yet done is systematically occupy the full range of market-making opportunities across platforms, categories, and deal structures that currently exist. That gap defines the entry window.
The calendar concentrates the stakes considerably. The POLY token launch drives a surge in retail participation and new market creation velocity. US midterm primaries beginning Q2 2026 will grow political event volume by 3x — 5x.
Hyperliquid HIP-4 mainnet arrival in Q3 2026 opens a new venue at the ground floor. The November 2026 midterm elections are the peak liquidity event of the year, rewarding operators who arrive with calibrated models and pre-positioned capital across the key markets.
Every month of delay is a month of compounding disadvantage in a market where reward structures favor incumbents, where track record drives institutional access, and where the professional layer is still thin enough that a well-resourced operator can establish genuine market presence before the window closes.
What the Numbers Actually Look Like
Three scenarios frame the range of realistic outcomes for a production-tier entry. The conservative case, which Cicada Market Making assigns approximately 60% probability, deploys $300K of initial capital with a three-person team, reaches breakeven at month 5, and generates $300K — $500K in Year 1 P&L representing 100% — 170% return on deployed capital.
The base case, at 30% probability, scales to $200K — $350K per month by months 12–18 as the first structured product launches, with Year 2 P&L reaching $3M — $6M on 20M+ in AUM. The aggressive case, at 10% probability with $5M+ of initial capital and an anchor LP secured by month 12, targets $8M — $15M in Year 2 P&L on $80M — $150M in AUM.
The most sensitive variable across all scenarios is MM edge in basis points, where a 20% compression translates directly to 25% reduction in Year 1 P&L. Platform volume and Polymarket’s reward rate each carry 15% — 20% sensitivity, while capital deployment efficiency contributes another 18%.
On the risk side, the four areas requiring active management are adverse selection from informed traders on political markets, regulatory action against either dominant platform, Polymarket reward structure changes post token launch, and TradFi competition arrival compressing margins in the most accessible strategies.
Each has a defined mitigation path, and collectively they reinforce the same conclusion: the earlier the entry, the more favorable the risk profile.
Conversation with Outcome Labs
We sat down with Jonathan, Chief BDO at Outcome Labs, to get an operator’s view on what actually differentiates on-chain prediction markets from traditional bookmakers, and where the next wave of volume is likely to come from.
Q: What does an on-chain prediction market give a trader that a traditional bookmaker fundamentally can’t?
It’s a matter of who the counterparty is. A bookmaker would set odds to protect their margin, and the model depends on the house coming out ahead. In other words, they profit when you lose. Whereas an on-chain market would be more efficient, more visible, and fairer infrastructure precisely because you’re not competing with the house. You trade at a market-set price vs. other participants, with positions and payouts verifiable on-chain.Because more of the process is automated on-chain, the cost of executing that trade is more capital-efficient. Depending on the design, on-chain prediction market resolution mechanisms can be more closely related to the actual outcomes if you have multiple parties composing a resolution and involve verified oracles, in comparison to a centralized system which may be predisposed to manipulation or inaccuracies.
Q: Which category isn’t being priced yet but should be, and what’s the infrastructure gap holding it back?
At the moment, a large proportion of prediction market volume is sports, given the general population’s interest in it and the analogs they share with sportsbooks, making them easier to understand intuitively for a retail audience. In the future, as liquidity increases, you should see prediction markets become a primitive that is relevant for institutions. For example, you can expect economics and politics to grow as discretionary macro hedge funds arrive in the coming years. They would just require trading infrastructure such as prime brokers to enable them to trade safely. Another large unlock would be leveraging prediction markets for real-world risk, such as insurance-style, parametric markets around weather and natural disasters, the kind of Property & Casualty (P&C) exposure insurers typically want to hedge with reinsurers.Right now, what’s preventing institutions from entering, as you mentioned, is infrastructure. Hyperliquid is unique in that its back-end will be white-labeled across many builder-code front-ends. Wallets, exchanges, trading terminals, and prime brokers that incorporate Hyperliquid should readily have access to HIP-4 already within a cross-margin setup. Being able to access a thick order book with minimal fees will enable increased adoption of that order book across multiple distribution channels. With the increased adoption of Hyperliquid builder codes, that should only be a matter of time.
Q: With most platforms looking similar on the surface, where’s the real moat: liquidity, resolution infrastructure, or distribution?
All of those matter, but in a world of multiple prediction markets, having the order book readily available through multiple distribution channels increases the chance of network effects and higher usage. Liquidity for contracts will ensure flow continues to come, which acts as a flywheel. The resolution infrastructure is important for the whole system to feel fair and for users to feel respected — that funnels into brand transparency.Not all prediction markets will be built on Hyperliquid, which is some of the most efficient trading infrastructure with minimal cost bloat (i.e., a 13-person team) and is able to benefit from the value of the HYPE community, for which there are sufficient revenues going back towards buyback pressure. HYPE is likely one of the only success stories in crypto that was able to successfully engineer tokenomics in a way that encourages organic marketing. Hyperliquid is already on the path towards cementing its position within on-chain trading, including spot and derivatives, which many perps platforms have tried and failed to recreate during the past meta. Hyperliquid has already reached a degree of escape velocity with its DAT listings, coverage by Wall Street, and increased presence, which leads to widespread adoption through more seamless conversations (e.g., with builder codes rather than manual business development deals).You’ve seen prediction markets such as Kalshi and Polymarket both announce attempts to enter the perps space. The market already understands how difficult it is to enter perps and recreate the same flywheel Hyperliquid created, given its lack of venture funding (and the resulting lack of typical token-dumping pressure), and the benefits set up for market makers (e.g., cancel priority, speed bumps), among others. By leveraging existing infrastructure that already has market makers plugged in, the ability to cross-margin positions, and the increasingly wide distribution scope that builder codes provide, HIP-4 should have a more intuitive and natural path towards building adoption.
Taken together, these answers reinforce the report’s core thesis: liquidity, resolution, and distribution aren’t separate moats, they compound on each other, and platforms stacking all three early are the ones positioned to absorb the next leg of volume.
Maxim Moris’s Vision, CEO of Cicada
We also asked Maxim Moris, Cicada’s CEO, for a more candid, on-the-ground read on platform dynamics and what’s actually likely to move volume through the rest of 2026.
Q: Which emerging platform has a realistic shot at capturing at least 10% of the market by the end of 2026?
Kalshi’s success in the US makes sense in context: the country never had the kind of established betting industry Europeans grew up with, so Kalshi simply walked into an open niche. A lot of the platforms trying to copy that playbook elsewhere miss this entirely — in most other countries, that niche has been occupied by traditional bookmakers for decades.You see it directly in the even around an event as massive as the World Cup, many Polymarket and Kalshi clones still struggle to attract real liquidity, because users are already anchored to other platforms. Polymarket’s own growth, meanwhile, has been driven in no small part by informed and insider-adjacent flow, which is clearly bad for market integrity, but doesn’t change the underlying demand: people like to bet, the population prone to it isn’t shrinking, and on-chain prediction markets fit naturally into crypto’s broader trajectory.Over time this market will accumulate more rules and more regulation, and that’s exactly the environment new entrants need to find real footing.
Q: Are the US midterms the only major volume driver this year, or are there hidden catalysts?
The midterms are the obvious, scheduled catalyst, but the less obvious one is structural rather than calendar-based: as long as informed flow and insider-adjacent trading keep pulling sophisticated capital toward these platforms, and retail gambling demand keeps growing rather than shrinking, volume gets pulled forward independent of any single event on the calendar. The midterms will spike attention, but the underlying growth curve is being driven by participation dynamics that don’t reset after election day.
Q: Will short-term 30-minute crypto price contracts become more popular than traditional event markets?
No — they serve a fundamentally different class of trader. Short-dated crypto contracts attract people thinking in options-like, intraday terms, while event markets attract people with a view on a real-world outcome. They’ll grow in parallel rather than one displacing the other.
That mix of structural inefficiency, sticky user habits, and a regulatory framework still being written is, in Maxim’s view, exactly what makes this window worth moving fast on now rather than waiting for the rules to fully settle.
The Thesis
Prediction markets have reached the scale and regulatory legitimacy that makes them a genuine asset class. The current structure, with retail participants losing systematically to a thin professional layer while institutional capital forms but remains largely without proper access infrastructure, describes a market in early transition.
The opportunity for an operator with existing algorithmic trading expertise runs across three time horizons. Near-term cash flow comes from market-making and arbitrage strategies that reach profitability within weeks of deployment.
Medium-term margin expansion comes from OTC operations and cross-platform capital strategies that layer on top of a running infrastructure base. Long-term operating leverage comes from structured products that monetize the institutional access gap with margins that resemble software businesses rather than trading desks.
The infrastructure required to enter is accessible, the market structure is genuinely favorable, and the regulatory environment has cleared. The window is real and it is closing.
Read more: YOM: DePIN for Cloud Gaming

| Featuring insights from YOM, Up10 & TokenLockr.
YOM is a decentralized cloud gaming network built on the DePIN model: Decentralized Physical Infrastructure Network, where independent operators contribute real GPU hardware from real locations around the world to power game sessions on demand.
The network runs on three participants. Players generate demand through gameplay. Publishers distribute game content into the system. Operators contribute the GPU resources that power execution. Each role feeds the others, sustaining a gaming economy built around distributed rendering and instant access.
Game sessions start the moment a player clicks. The infrastructure lives at the edges of the network, contributed by people who own hardware and choose to put it to work inside the YOM ecosystem.
Rendering Network Built for Real Time
At the heart of YOM sits a GPU network purpose-built for pixel streaming and real-time game execution. Operators connect their hardware into a shared compute layer that absorbs rendering, simulation, and encoding workloads as they arrive, processing them across nodes continuously.
When a player starts a session, the AI orchestration system called HyperOrch evaluates the network and routes the workload to the most suitable node available. The decision happens in milliseconds, invisibly, before the first frame appears on screen.
Gameplay streams back via WebRTC with continuous input and output synchronization. The player interacts with a live render running on hardware spread across the globe, experiencing a responsive session regardless of the device in their hands.
Blockchain as the Coordination Layer
Keeping thousands of independent GPU nodes honest and synchronized requires infrastructure that operates without a central authority. YOM uses blockchain as that backbone.
Every compute contribution gets recorded on-chain, every workload execution is tracked, and reward distribution flows automatically according to protocol rules.
Three core functions it handles across the network:
Verification of rendering tasks across GPU nodesSynchronization of session state as workloads move dynamicallyEnforcement of incentive rules tied directly to performance and reliability
Game sessions travel fluidly while execution consistency holds, because the coordination layer absorbs that complexity at the protocol level.
Operators: The Backbone of Execution
Operators are the people and organizations providing the GPU hardware that powers YOM. Every frame rendered, every physics simulation run, every video stream encoded flows through their machines. The network exists because operators choose to participate in it.
This is the DePIN model in motion. Hardware contributors earn rewards by serving real demand, and the network grows stronger with every new participant. Each operator feeds into a shared execution pool handling the full range of workloads required to deliver gameplay across every active session.
Operators are evaluated on:
Uptime and availability under sustained loadRendering reliability and frame consistencyResponsiveness to workload allocation from the orchestration layerOutput quality under real-time conditions
GPU hardware becomes an active, performance-driven component of the gaming economy, with real consequences attached to how well it performs.
Economics of Distributed Gaming
The performance of the network feeds directly into its economics. Instant game access generates demand for rendering capacity, which creates incentives for operators to contribute GPU resources.
As participation grows, available compute expands and the experience improves for players. More players engage, demand grows further, and the cycle accelerates.
Operators can engage through direct GPU operation, delegated compute participation, or node licensing systems that allow scalable infrastructure deployment without requiring enterprise-scale hardware management.
$YOM Economy and Incentives
The $YOM token is the core coordination and settlement asset across the network. It ties GPU supply, gameplay demand, and operator rewards into a single unified structure that governs how value moves through the system.
Total supply is fixed at 750,000,000 $YOM. The TGE price was set at $0.10, putting the fully diluted valuation at $75,000,000.
At launch, approximately 19.8% of total supply entered circulation, with the remainder distributed through multi-year vesting cycles. The token runs on Avalanche, with cross-chain distribution enabled through LayerZero.
Token allocation breaks down as follows:
Treasury: 37.5%Ecosystem and operator incentives: 25%Long-term holder allocation: 17.31%Liquidity provisioning: 9.72%Team allocation: 3%Seed, private, KOL, and community
Operator rewards connect directly to real network usage, with payouts tied to session execution, uptime, and rendering delivery. The emission schedule runs approximately four years, with structured vesting and burn logic tied to compute execution creating downward pressure on circulating supply.
The TGE occurred on June 5, marking the transition into live token distribution and active network incentives across operators, publishers, and players.
IDO on Up10 Launchpad
The public sale ran through Up10 at a token price of $0.07, with participation limits set between $50 and $1,000 per user. The sale opened on May 27, raising $50,000 and reaching sold out.
Access ran through standard launchpad protection mechanisms, including allocation caps and anti-bot measures. A dynamic refund system offered up to 80% protection during the sale and full refund coverage in the event of a failed listing, keeping conditions controlled and access fair throughout.
The Up10 sale functioned as one segment of the broader TGE, sitting alongside ecosystem allocations, operator incentives, treasury distribution, and vesting-based team allocations.
Insights from CEO of Up10
To gain additional insights into token launches and community growth in Web3, we spoke with Denis Umet, CEO of Up10. We discussed participant distribution, post-launch engagement, and the principles behind building long-term ecosystem value.
Q: For a project like YOM, what matters more during launch: speed of sellout or quality of participant distribution?
“For Up10, quality of participant distribution matters more than sellout speed. A fast sellout may generate attention, but concentrated allocations often create weak post-launch dynamics.Projects like YOM benefit more from attracting participants who are aligned with the ecosystem over the long term, including node operators, gamers, and infrastructure supporters. In that sense, sellout speed is a vanity metric, while holder quality is a sustainability metric.“
Q: How do you maintain community engagement after an IDO campaign ends?
“Our approach is to build around motivated users rather than short-term capital. Community engagement continues through product updates, integrations, network growth metrics, and ecosystem milestones.For YOM, that means highlighting node operator activity, new games entering the network, and measurable DePIN adoption. The focus remains on utility and execution rather than short-term market movements.“
Q: What makes the $YOM distribution through Up10 different from a standard IDO launch?
“Most IDOs operate as a simple sale event. With Up10, the distribution model is designed to align incentives between projects and participants over a longer period of time.For a DePIN network like YOM, this increases the likelihood that tokens reach users who actively contribute to the ecosystem, including operators, gamers, and strategic partners. The result is a distribution model built around network growth and trust rather than short-term speculation.“
These insights reflect a broader focus on long-term ecosystem growth, where participant quality, network adoption, and sustainable expansion matter more than short-term fundraising metrics.
Creator Campaign on TokenLockr
Growth coordination inside the YOM ecosystem runs through TokenLockr, a platform built around smart contract campaigns where creator rewards distribute through programmable conditions rather than manual agreements.
The first official YOM campaign allocates a reward pool of 200,000 $YOM, running from June 3 to June 29. Participants produce content about YOM and receive guaranteed payouts tied directly to their TokenLockr tier, with KPI-based bonuses unlocking as $YOM hits price targets.
Key points on the YOM campaign:
Guaranteed rewards based on your TokenLockr tierExtra $YOM rewards as the token hits price targetsPrice targets for KPI rewards: $0.15 / $0.20 / $0.30 / $0.40
The entire system operates as a single incentive loop, where every action inside the campaign feeds into the same outcome.
Insights from Founder of TokenLockr & Up10
To better understand the strategy behind the launch infrastructure and creator-driven growth systems, we spoke with Maxim Moris, Founder of TokenLockr and Up10.
Q: Why did you choose YOM as one of the first case studies for TokenLockr and Up10?
“YOM is a real infrastructure project that delivers tangible value. It is not just a speculative idea, but a functioning DePIN-based system with real assets behind it.We are proud to be partners with YOM on this journey. The project already has a strong and active community, which has also been very helpful for us through shared audience and ecosystem exposure.Overall, we see significant long-term potential for continued growth, both on the community side and the technological side.“
Q: How is the balance between guaranteed and KPI rewards structured within the YOM campaign design?
“The reward structure is designed so that every creator receives guaranteed compensation for their contribution. Approximately 50% of the total pool is allocated to fixed rewards distributed across all participants.The core idea of TokenLockr is that creators are always rewarded for producing content. There is no leaderboard system or points-based competition. Instead, rewards are assigned based on tier and content contribution.The remaining portion of the pool is used for performance-based incentives, aligning creators with the growth of the token. Since creators play a key role in driving awareness and adoption, they are fairly rewarded for that impact.“
Q: What does the $YOM launch through Up10 + TokenLockr reveal about coordination between launchpad mechanics and growth systems?
“Launching through Up10 together with TokenLockr is exactly the synergy we aimed to achieve. The goal was to make our internally built platforms work together as a unified system.Up10 is used for the launch process, while TokenLockr handles token and project promotion through creator campaigns. This combination has proven to work very effectively in practice.Our teams are in constant communication and closely support each other, operating almost like a single organism across both platforms. This is exactly the type of coordinated launch system we wanted to build.Early results from our first projects show that the model works as intended. There are no major issues, only minor areas for refinement based on real usage.We are confident this system will continue to improve over time, and based on the first case, we already see a strong foundation for scaling and further optimization.“
This perspective highlights a consistent direction across both platforms: a focus on real infrastructure, aligned incentives, and tightly integrated launch and growth mechanisms.
Team Behind YOM
YOM is built by a team with backgrounds across gaming, real-time systems, infrastructure engineering, and digital platform development. The founding group brings deep technical and operational experience in building scalable systems for high-performance workloads.
The project grew out of direct experience with the constraints that centralized GPU systems create around cost, latency, and scalability as demand grows. That experience became the foundation for a model built from the ground up for real-time game execution and streaming.
Insights from the YOM Team
To better understand the technical foundations behind a distributed cloud gaming network, we spoke with the YOM team. The discussion focused on what actually drives gameplay quality, how network stability is maintained at scale, and the core engineering challenges behind real-time streaming across a global operator network.
Q: Bigger impact: operator hardware vs HyperOrch orchestration?
“Both matter, but orchestration is the real differentiator. Strong operator hardware (GPU + bandwidth) defines the upper limit of what a single session can achieve. Every rig must pass RigCheck certification before joining the network: over 30,000 checks across 118+ countries, with only ~20% meeting the AAA streaming threshold.However, HyperOrch is what turns independent machines into a unified system. It evaluates latency, node load, and player location in real time, selecting the optimal node for each session in milliseconds. Hardware defines the ceiling; orchestration ensures that ceiling is consistently reached across the entire network.“
Q: Key factor for day-to-day operator-network stability?
“Stability comes from two layers working together: first, strict entry standards through RigCheck certification ensure only verified hardware and connectivity can serve live sessions. This prevents weak nodes from entering the routing pool.Second, HyperOrch dynamically routes each session based on real-time latency, load, and location data, continuously optimizing performance as conditions change. The system also improves over time by learning from session data.As a result, the network currently maintains a 99.2% session success rate (30-day average), sub-12ms global median latency, and under 0.1% packet loss.The next step is continuous real-time node health scoring with automated failover, allowing the system to proactively avoid degraded nodes before user experience is affected.“
Q: Hardest part of syncing WebRTC streaming across a global operator network?
“The biggest challenge is low-latency connectivity and NAT traversal at global scale. Because operators run on consumer-grade internet connections behind different NATs and firewalls, reliably establishing direct WebRTC paths across regions is complex.At the same time, the system must maintain extremely low latency for both video streaming and input synchronization, targeting sub-10ms performance.The challenge is bridging the gap between a system that works in controlled environments and one that feels fully native in any browser, without installs or friction.“
These answers highlight a consistent technical philosophy behind YOM: strict quality control at the hardware layer combined with real-time orchestration at the network layer.
Rather than relying on raw compute alone, the system is designed around intelligent routing, continuous optimization, and infrastructure-level reliability metrics.
Conclusion
YOM is a unified DePIN system where GPU infrastructure, protocol-level coordination, and incentive-driven participation operate as a single machine.
Game execution becomes a shared process, where rendering and streaming occur across a global network of operators working through protocol-level rules.
The vision is cloud gaming as a continuously evolving compute economy. As the network grows, performance scales with it. That is the feedback loop YOM is built around.