# FLock Open Model Offering (FOMO): step-by-step guide

> We’re excited to introduce FOMO (FLock Open Model Offering), a new protocol layer that completes the demand side of the FLock ecosystem.

**Published by:** [FLock.io Blog](https://paragraph.com/@flockio/)
**Published on:** 2026-01-19
**Categories:** ai, web3, crypto, decentralised, decentralized
**URL:** https://paragraph.com/@flockio/flock-open-model-offering-fomo-step-by-step-guide

## Content

Find the Chinese version here / 中文版本 and the Korean guide here / 한국어 번역본은 여기에 있습니다 In traditional AI infrastructure, pricing is rigid and upside is centralized. As usage grows, costs scale linearly, and the value created by developers and power users is largely captured by intermediaries. This model works for hyperscalers, but it breaks down for AI-native products, domain-specific models, and teams that rely heavily on inference as a core input. FOMO flips this structure by enforcing a simple principle: value only flows when real usage happens. Models are launched through a Real Model Asset Offering, where users and RMAs supporters commit capital to fund a concrete deployment. Tokens are not minted upfront. Only if the launch meets its funding threshold does the model graduate, tokenize, and proceed to deployment. If it doesn’t, the launch simply doesn’t exist. Find FOMO on fomo.flock.io. Once deployed on the FLock API Platform, the model begins serving real inference. From that point on, usage becomes the only signal that matters. Inference revenue is routed programmatically to buy back the model’s token, buy back the network token, fund ongoing operations, and reward the model operator. Early incentives help bootstrap adoption, but they decay over time as organic usage takes over. If a model isn’t used, rewards naturally disappear. This design is intentional. FOMO is not a speculative launchpad, and it does not attempt to manufacture demand through emissions alone. Each model deployment becomes its own small, transparent economy, where incentives align around adoption rather than narrative. Power users are rewarded for driving real demand, operators are incentivized to maintain competitive pricing and quality, and the protocol remains sustainable without propping up idle capital. FOMO also completes the loop with AI Arena, FLock’s decentralized training platform. AI Arena incentivizes the production of intelligence, while FOMO incentivizes its dissemination and use. Together with the API Platform, they form a full-cycle DeAI system where training, deployment, and consumption reinforce one another. This is just the beginning. As more models are launched through FOMO and more inference flows through the API Platform, we’ll continue refining the mechanisms that turn real usage into aligned economic outcomes. If you’re building with AI, operating models, or scaling inference-heavy applications, FOMO is built for you. Stay tuned as it rolls out across the FLock ecosystem.Step-by-step guideThis guide walks through the FOMO launch lifecycle from both sides:Real Model Asset (RMA) Issuers launching a modelUsers and RMAs Supporters participating in a model’s fundraisingFor RMA IssuersStep 1: Select a ModelGo to the Launch page.Select your desired model.Each model corresponds to a predefined inference pricing tier and an allowed fundraising range. These parameters are fixed by the platform to ensure economic sustainability.Step 2: Configure Your Model Token ($MT)Configure $MT economics:Name your deployment and define:Model token nameTicker symbolDescriptionReview the pre-configured parameters, including:Inference pricing tierFundraise min / max rangeToken distribution summaryThese values are automatically populated based on the selected model and cannot be arbitrarily changed.Step 3: Bundle the First Buy Order (Optional)RMA issuers may choose to bundle an initial token purchase at launch.This provides a first-mover advantage by locking in the lowest point on the bonding curveThe first buy is executed atomically with token deployment, removing market-timing riskThe bundled first buy is subject to a hard cap of 25% of the total $MT supply to prevent excessive concentration at launch. Note: The bonding curve applies throughout the entire fundraising period, dynamically pricing tokens as demand evolves — not just at launch.Step 4: Confirm Launch FeeBefore initiating the Real Model Asset Offering (RMO), the RMA issuers must confirm and approve the launch-related fees. This confirmation is required to proceed with model deployment and on-chain configuration.One-time launch fee. A fixed, non-recurring fee of $32768 FLOCK payable by the RMA issuers at the time of initiating the RMO. This fee covers deployment setup, onchain configuration, and protocol overhead associated with launching a new model economy.Combined tax (base fee plus anti-sniping tax) starts at 99% and decreases by 1% per minute, until it reaches the base fee.Step 5: Launch the Model TokenOnce confirmed:The RMO is createdThe fundraising period 7 days beginsTokens are not minted during fundraising periodYou can now find your deployment on the Marketplace page.Status indicators:Owned — launched successfully by youLive — fundraising in progressFailed - fundraising target not met and pledged principal refundedStep 6: Fundraising PeriodFundraising remains open for 7 daysProgress toward the minimum and maximum targets is tracked in real time (please refer to “Fundraise Outcomes” section for details)No action is required during this periodFor Users and RMAs SupportersStep 1: Discover a Model TokenNavigate to the Marketplace page.Browse available model deployments and select a model token you want to support.Step 2: Participate in the FundraisingSwap $FLOCK → $MT via the bonding curveToken price increases as more $FLOCK flows inA 1.5% platform transaction fee applies to each swapNote: $MT purchased during fundraising cannot be sold back into the internal market during fundraising period.Step 3: Wait for Fundraise OutcomeThe fundraising remains open for a fixed period.Progress toward the minimum and maximum funding targets is tracked in real time.No further action is required until the fundraising concludes.Fundraise OutcomesScenario 1: Happy Path — Maximum Target ReachedGraduation is triggered automaticallyTokens are mintedLiquidity is createdThe model proceeds to deploymentScenario 2: Happy Path — Minimum Target ReachedGraduation must be triggered manuallyGraduation is permissionless that anyone can trigger itAction:Click “Graduate Token” to launch the liquidity poolScenario 3: Unhappy Path — Minimum Target Not ReachedThe fundraise failsTokens are not mintedAction:Click “Redeem” to reclaim fundraised $FLOCKLaunch fees and transaction fees are not refundable. Only the pledged $FLOCK principal is returned.After GraduationOnce graduated:The model token becomes tradableMarketplace status updates to “Tradable on Deluthium”Clicking the token redirects users to the Deluthium swap pageNote: Deluthium is currently not available in the USFrom this point forward:The model will be deployed on the FLock API PlatformInference usage drives revenue, buybacks, and rewardFind the Chinese version here / 中文版本

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