These simulations model a 3,000 GRAM funding goal over 72 hourly uniform-price clearing periods. Each scenario has the same token supply, same time window, and the same top-bid reference (the highest active max price each period). What changes is the shape of bidder demand.

Key takeaways

• Front-loading raises the most in absolute terms but commits far more capital than it converts (low raised/committed ratio).
• A slow start is risky: late demand cannot lift earlier low clearings, so the VWAP and efficiency both suffer.
• Random whales gave the best raised/committed ratio (36%) because high-max bids raise the clearing that everyone pays.
• Bidders should bid their true max price; in uniform-price auctions, everyone pays the clearing, so a higher max does not overpay.
• Each wallet is capped at 2% of the total token supply, so capital concentration and high max prices matter.
• The top-bid reference tracks the highest active max price each period, anchoring new entrants to live demand rather than the last clearing.

Watch a 72-minute uniform-price auction loop in real time. The mock restarts every 75 minutes (72 minutes of auction plus a 3-minute cooldown) so you can observe the price chart, period clearing, and bid flow from start to finish.

Open live simulation →

Switch between the three demand patterns to compare the clearing-price charts, period logs, and filled-bidder tables.