This dataset complements the following publication: Goldberg, D.E. & Haynie, K.L (2021) Ready for real-time: Performance of Global Navigation Satellite Systems in 2019 Mw7.1 Ridgecrest, California, rapid response products, Seismological Research Letters, doi: 10.1785/0220210278. The availability of low-latency, high-rate Global Navigation Satellite Systems (GNSS) waveforms makes it possible to compute joint seismic and geodetic finite-fault models of significant earthquakes (typically M 6.0 or larger) using regional data (i.e. from strong-motion accelerometers and real-time GNSS). Notably, real-time GNSS displacement data has reduced accuracy when compared to post-processed displacements, due to inherent challenges in estimating satellite clocks and orbits in real-time (see associated manuscript for details). Here, we present the results of joint strong-motion accelerometer and GNSS finite-fault inversions for the 2019 Mw7.1 Ridgecrest, California, earthquake. We compare the results of the joint inversions that use post-processed GNSS to those making use of real-time GNSS displacements. Real-time GNSS displacements come from two different processing facilities: UNAVCO and Central Washington University (CWU). Two different weighting schemes (uniform and data norm weighting) are applied, resulting in a total of six joint inversions. A figure showing these six models is included here ("Finite-Fault Model Results") and is a reproduction of Figure 3 of the associated manuscript listed above. The inversion results are provided as text files with titles corresponding to their GNSS data processing type and the inversion data weighting scheme (e.g., "Strong-Motion and CWU Real-Time GNSS (Uniform Weight)." Please see the associated manuscript listed above for details about the GNSS processing types and weighting schemes applied. A summary table comparing the six models (above) and the USGS teleseismic inversion (https://earthquake.usgs.gov/earthquakes/eventpage/ci38457511/finite-fau…) is titled "Finite-Fault Model Comparison Summary". The resulting models are also used to create an estimate of the source dimensions as input to the USGS ShakeMap ground motion estimates. Estimated source dimension information is available in the table titled "Source Dimension Estimates for ShakeMap".