# Points Allocation Quarkduck Points Allocation & Distribution: 1\. Flat: Each Quarkduck NFT garners a uniform reward of 10,000 Quarkduck Points per block. 2\. Incentive: * Early Bird Incentives: Early participants will benefit from a multiplier boost to their Quarkduck Points, ranging from 2x to 8x. The multiplier begins at 8x and diminishes by one with each incentive cycle (equivalent to 144 blocks), bottoming out at 2x. For instance, the initial cycle post-mint will yield 8x10,000 Quarkduck Points per block, with subsequent cycles decreasing sequentially until the seventh cycle concludes. * Diamond Hand Incentives: In the concluding phases of point mining, there are 14 incentive cycles, beginning with a 1.5 times multiplier and escalating by 0.5 times each cycle until reaching an 8 times multiplier. For instance, during the final cycle (mining blocks 9856 to 10000), each block will yield 80,000 Quarkduck Points. The cycle immediately before this (mining blocks 9711 to 9855) will produce 75,000 Quarkduck Points per block, continuing in this manner down to the fourteenth cycle from the end. 3\. Random: Random rewards hinge on two factors: the SERIES of your Quarkduck and the block hash value. If your Quarkduck's lucky number aligns with the block's lucky value, it mines an additional 160,000 Quarkduck Points in that block. * **Block Lucky Number: Calculated as the last four hexadecimal digits of the block hash converted to decimal, modulo 21.** * **Quarkduck series, subject to data queried on the official website.**
4. Boosted: A singular boost will be accessible to all Quarkduck NFT holders. Further details will be disclosed subsequently. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://guide.quarkduck.com/aft-allocation-system/points-allocation.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.