> For the complete documentation index, see [llms.txt](https://whitepaper.usegpu.app/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://whitepaper.usegpu.app/conclusion.md). # Conclusion Summarize the USE-GPU model, its fee-funded mining foundation, planned GPU infrastructure, and the progression toward developer-facing compute. USE-GPU is a fee-funded mining ecosystem designed to evolve toward physical GPU infrastructure. It starts with trading activity and token-based mining. Physical compute is introduced progressively through treasury resources. ``` Trading activity ↓ Creator fee ↓ Treasury ↓ Token mining ↓ GPU acquisition ↓ GPU infrastructure ↓ GPU rental ↓ Inference services ``` The model intentionally begins before the physical GPU layer. Initial yield comes from trading activity, not GPU computation. ### The model in one view #### The initial layer The USEGPU token launches through pump.fun. Trading activity generates a 0.30% creator fee, which becomes the ecosystem's initial economic input. The fee allocation supports mining, the GPU Treasury, holder sharing, buyback and burn, and operations. This structure connects present participation with treasury formation. #### The mining layer Participants lock USEGPU tokens and time to generate mining power. Mining power determines each participant's proportional share of the Mining Pool. The Mining Pool receives its initial funding from creator-fee revenue. Rewards are variable because they depend on trading activity. There is no fixed APY, and mining does not require GPU computation. #### The infrastructure layer Phase 1 has no GPUs. The GPU Treasury is intended to fund the first hardware acquisition as it accumulates. Phase 2 targets two NVIDIA RTX 4090 units at approximately $2,000 each. These are roadmap targets. The project plans to publish hardware and operational information once deployment occurs. #### The compute layer Phase 3 plans to expand capacity through external GPU operators. Operators receive 70% of rental fees. Phase 4 plans to introduce an inference API. Developers pay per token of compute. Later GPU rental and inference-service revenue can contribute to the Mining Pool. ### Yield before hardware USE-GPU does not begin by building a GPU network and then seeking economic activity. It starts with a fee-funded mining mechanism and intends to use treasury accumulation to introduce physical compute infrastructure over time. The defining progression is: ``` Economic activity → participation → treasury → hardware → compute services ``` The infrastructure thesis depends on the economic layer working first. ### Current model and roadmap **The initial model includes:** * Solana-based token infrastructure * The pump.fun creator-fee mechanism * Fee allocation, token-based mining, and treasury accumulation * A roadmap toward GPU infrastructure **The following remain planned:** * First physical GPUs and deployment * External GPU operators and rental expansion * An inference API and developer compute usage The model is intentionally presented in stages. The mining economy comes first. Physical infrastructure follows. Developer-facing compute comes later. ### Economic reality Mining rewards depend on trading activity. Lower activity means less creator-fee revenue, lower Mining Pool funding, and slower treasury accumulation. Stronger activity can increase creator-fee revenue, Mining Pool funding, and treasury accumulation. The market determines trading activity. The transition toward GPU infrastructure also depends on treasury accumulation and execution. USE-GPU does not currently have GPUs in Phase 1, an NVIDIA partnership, a pump.fun partnership, fixed APY, or guaranteed mining returns. ### Roadmap synthesis ``` Phase 1: Mining First Establish the fee-funded mining economy and treasury ↓ Phase 2: First GPUs Convert accumulated treasury resources into physical GPU infrastructure ↓ Phase 3: GPU Operators Expand available GPU capacity through external contributors ↓ Phase 4: Inference API Turn GPU capacity into developer-facing compute services ``` The intended model is a system where trading activity funds participation, treasury resources fund infrastructure, infrastructure generates compute revenue, and compute usage can add revenue to the ecosystem. This is the planned progression, not a guaranteed outcome. Use the GPU. Mine the yield. --- # 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 dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://whitepaper.usegpu.app/conclusion.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.