> For the complete documentation index, see [llms.txt](https://paper.chainopera.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://paper.chainopera.ai/tokenomics-and-protocol-design/burn-and-mint-equilibrium-model-old.md).
# Burn and Mint Equilibrium Model (old)
We introduce an advanced version of the Burn and Mint Equilibrium Model (BME) for collaborative machine learning. In the ChainOpera ecosystem, consumers request AI services—including AI agent interactions, model inference, and model training—from a decentralized network of AI infrastructure suppliers. Consumers pay in fiat currency and burn a variable amount of tokens to access these services, while suppliers receive a combination of fiat currency and tokens. The number of tokens that consumers must burn depends on both the current token price and job price. Similarly, supplier rewards are distributed according to a dynamic emission schedule and each supplier's contribution to ML services.
For the complete documentation of the BME model in ChainOpera AI, please refer to [this detailed document](https://docs.google.com/document/d/1uoYLLVG3NxcvvmgVe2Huog-xSY4INMb8zWzfKBlDfc4/edit?tab=t.0) (requires permission from the ChainOpera team).
---
# 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://paper.chainopera.ai/tokenomics-and-protocol-design/burn-and-mint-equilibrium-model-old.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.
