We improve the accuracy of Active Volume (AV) resource estimates by explicitly scheduling when AV blocks execute and when their reactions complete. We present a cycle-accurate scheduler that assigns each logical qubit a role in every logical cycle. The approach allows us to capture execution effects such as gate packing inefficiencies, parallelization overhead, and memory requirements. In addition, the scheduler explicitly tracks reaction latency and stale state lifetimes, rather than assuming that stale states can be absorbed into a fixed overhead. For a 4×4 Fermi–Hubbard test circuit, we find a transition to reaction-dominant regime at approximately 10³ logical qubits. Beyond 10³ logical qubits, stale state accumulation restricts the effective workspace and the benefit of adding more qubits is substantially decreased. Below this regime the scheduler predicts a 1.64× runtime speedup relative to the previous Analytic Resource Estimators (ARE), primarily due to a 1.80× reduction in average memory occupancy. We also show that parallelization and reaction latency overhead grows with available workspace, inverting the trend of the ARE model used in . These results provide a path toward reaction-aware analytic resource estimates and a full compilation pipeline for AV architectures. We also develop novel techniques for estimating Y state and routing demand and apply them to our test circuit. The Y state estimates result in small efficiency boost and the routing demand estimates show that routing should not bottleneck early fault-tolerant AV devices.