Just because a quantum computer produces a valid answer doesn't mean it produced the best one. And I think that distinction matters more than people realize. Been digging into how @quipnetwork approaches this with QVM on the Aglais testnet. Through xQuad, developers describe optimization problems as constraints. The compiler then creates an encoder, verifier, and decoder to handle the workflow. Here's the interesting part: A verifier can help determine whether a result satisfies the required conditions. But satisfying the rules and finding the optimal answer are two different things. Even hardware attestation only tells you where the computation happened. It doesn't prove the result couldn't have been better. So for me, the meaningful comparison comes down to: - Solution quality. - Execution speed. - Actual cost. QVM currently supports CPU, GPU, and D-Wave backends, with IBM and IonQ planned for later. That's enough to start asking some interesting questions. Will quantum hardware deliver better solutions? Will classical systems remain cheaper or faster for certain workloads? Or will the best choice depend entirely on the problem? I'd rather see those comparisons than another headline about how many machines a network supports.