> For the complete documentation index, see [llms.txt](https://docs.ig3.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ig3.ai/reward-mechanism.md). # Reward Mechanism The reward mechanism governs how rewards are distributed to edge nodes in each epoch. An epoch is defined as a one-week period starting from Thursday at 02:00 UTC and ending the following Thursday at 02:00 UTC. The TOPS token reward system is designed to encourage high performance, distributed, and honest behavior across edge device operators. It combines both deterministic and performance based components to incentivize optimal behavior. ``` TOTAL_REWARD_PER_EPOCH = BASE_REWARD_POOL + BONUS_REWARD_POOL ``` ### 🛠 Base Reward Pool ``` BASE_REWARD_POOL = BASE_REWARD * UPTIME_RATIO * TIER_MULTIPLIER ``` * `BASE_REWARD`: Static reward allocated per epoch. * [`UPTIME_RATIO`](/reward-mechanism/uptime-ratio.md): Float (0–1) indicating the percentage of time the node was online. * [`TIER_MULTIPLIER`](/reward-mechanism/tier-multiplier.md): Numeric multiplier based on device tier. Ensures fair distribution based on device availability and hardware contribution. ### 🎯 Bonus Reward Pool ``` BONUS_REWARD_POOL = EPOCH_POOL * STAKING_WEIGHT * AI_TASK_SCORE * DENSITY_BOOST ``` * `EPOCH_POOL`: Dynamic bonus pool assigned for the epoch. * `STAKING_WEIGHT`: Ratio of tokens staked on a device relative to others. * [`AI_TASK_SCORE`](/reward-mechanism/ai-task-score-and-machine-selection-algorithm.md): Performance-based score derived from completed AI tasks. * [`DENSITY_BOOST`](/reward-mechanism/density-boost.md): Incentive multiplier for operating in low-density regions. Rewards behavior that improves network quality: staking, compute contribution, and geographic decentralization. ### ⚠️ Reward Payout * Reward payouts are weekly, **every Thursday AFTER 2:00 AM UTC** once the epoch ends. * **Payout times vary by device**, so check your device screen for your specific reward receive date and time. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.ig3.ai/reward-mechanism.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.