In the field of Blockchain, how can we ensure the credibility of models or complex computational results that go live? Boundless offers a solution that makes "results verifiable on-chain" a quantifiable process. Here is a practical three-step guide:

First, perform small-scale task reuse. Decompose a model inference request into multiple small tasks, and then observe the reuse rate and single Gas cost on-chain. This step helps to understand the efficiency and economy of the system.

Secondly, conduct performance comparison tests. Use the same input to run on both the self-built environment and the Boundless platform, comparing the differences in latency, memory usage, and parallel processing capabilities. This helps to evaluate the actual performance advantages of Boundless.

Finally, conduct a price elasticity test. By gradually increasing task density, observe the market matching price, node response speed, and the stability of the ZKC payment link. This step can help understand the system's performance under high load.

During the evaluation process, some key indicators should also be focused on: proof replayability (whether replay verification is supported), the impact of proof size on on-chain costs, task sharding efficiency, and market depth (the number of independent order takers). Although short-term fluctuations in token prices may affect the data, these quantitative indicators can truly reflect whether Boundless can convert 'trusted computing power' into budgetable and auditable practical products.

Through this practical approach, developers and enterprises can objectively assess the utility of Boundless, providing a reliable basis for decision-making. This not only helps enhance the credibility of Blockchain computing but also promotes the entire industry towards a more efficient and transparent direction.