Quantum computers can run only a limited number of algorithms at a time, so you need to discard algorithms that require many resources.

Quantum computers are an expensive technology, so you need to estimate how much an algorithm will cost to make the best economic decision.

Resource estimation allows us to refine quantum solutions to run on future quantum computers by making choices about architectural design and QEC schemes.

You can pick from six predefined qubit models, and each of their values can be updated. You can modify existing models and create new ones.

You can pick from two predefined qubit models, the Surface code and the Floquet code.

You can pick from six predefined qubit models, but you can't customize their parameters.

The Resource Estimator outputs the estimated economic cost of running the algorithm and its runtime.

The Resource Estimator outputs the number of physical qubits and the runtime of a quantum algorithm for each of the quantum hardware providers that are available in Azure Quantum.

The Resource Estimator outputs physical and logical estimates, such as number of rotation gates, QEC estimates, T factory parameters, and total physical qubits and runtime.