Cooperative awareness (CA) and collective perception (CP) deal with the exchange of perception data within vehicle-to-everything (V2X). The achievable and needed accuracy is not yet analyzed in detail. The baseline for accuracy is the data from simulations, recommendations provided by standards, or various perception datasets with a disconnect between localization accuracy and perception accuracy. We extended a state-of-the-art (SOTA) automated driving (AD) platform with CA/CP functionality in our work. We then deployed it on two street-legal AD demonstrators (ADDs) and did an extensive field test to acquire data. With the data, we show the achievable accuracy of SOTA systems and discuss the requirements for future implementations.