Imaging methods in neuroscience are used to visualize and record neural activity from large cell populations. Within imaging modalities, miniaturized microscopes, which typically weigh < 4 grams, have become widely used and feature the added advantage of recording in vivo neural activity with unrestrained behavior. The current designs have shown exciting results from imaging fluorescent genetically encoded calcium indicators (GECIs) which have bright and slow dynamics (> 1 s) easily captured by most image sensors at frame rates of 30 Hz or less. However, there are many neuroscience applications which would benefit from using other emerging neural indicators, such as fluorescent genetically-encoded voltage indicators (GEVIs) that have faster temporal resolution to match neuron spiking, or bioluminescent indicators which can eliminate autofluorescence and photobleaching that occurs in fluorescent indicators. Despite their potential, miniaturized microscopes are not in use with these indicators likely due to their inability to image at high speeds to capture the fast dynamics of GEVIs and inability to image with high sensitivity required for signals with low signal to noise ratio (SNR) inherent to current versions of GEVIs and bioluminescent indicators. We addressed this problem by integrating the latest CMOS image sensor technology into a popular open-source miniaturized microscope platform. MiniFAST is a fast and sensitive miniaturized microscope capable of 1080p video, 1.5um resolution, frame rates up to 500-Hz and high gain ability (up to 70 dB) to image in extremely low light conditions. We also report results of high speed 500-Hz in vitro imaging of a GEVI and ~300-Hz in vivo imaging of transgenic Thy1-GCaMP6f mice. Finally, we show the potential for a reduction in photobleaching effects by using high gain imaging with ultra-low excitation light power (0.05mW) at 60 Hz frame rates while still resolving Ca2+ spiking activity. Our results extend miniaturized microscope capabilities in high-speed imaging, high sensitivity and increased resolution opening the door for the open-source community to use fast and dim neural indicators.