Magnetic resonance vascular fingerprinting (MRvF) enables the simultaneous measurement of quantitative oxygen saturation, cerebral blood volume, and microvascular radii maps from a single scan. Accelerating image acquisition for MRvF would enable new dynamic investigations into cerebrovascular diseases. Acquisition acceleration will result in tradeoffs between parameter map accuracy, time resolution, and noise. We performed a simulation study in which five signal-to-noise ratios and five echo train lengths were used to generate 25 simulated datasets to assess limits required for accurate matching. Vascular parameter matching accuracy increases with increased SNR and echo train length and requires an SNR above at least 20.