Satellite-based active fire data provide indispensable information for monitoring global fire activity and understanding its impacts on climate and air quality. Yet the limited spatiotemporal sampling capacities of current satellites result in considerable uncertainties in fire observation and emissions estimation. The mitigation of these uncertainties mainly relies on new remote-sensing technology. The Advanced Baseline Imager (ABI) onboard the Geostationary Operational Environmental Satellite-R (GOES-R) Series observes fires across North and South Americas at an unprecedentedly spatiotemporal resolution of nominal 2 km every 5–15 min. This study evaluated the GOES-16 (the first GOES-R satellite) ABI active fire product using active fire data derived from the 30-m Landsat-8 and the 375-m and 750-m Visible Infrared Imaging Radiometer Suite (VIIRS), and ground-based burning data across the southeastern Conterminous United States (CONUS) during the 2018 peak fire season. Specifically, we characterized the overall fire detection performance of the ABI active fire detections, estimated omission and commission errors, and evaluated ABI fire radiative power (FRP). The results showed that the ABI fire detection probability and its omission and commission errors were highly related to fire size and temporal period. ABI detection probability was higher than 95% for the fire pixel that contained over 114 Landsat-8 (30 m) fire detections or 11 VIIRS (375 m) detections. During a period of ±8 h, ABI detected 19% and 29% more fires observed by Landsat-8 and 375-m VIIRS, respectively. Correspondingly, the omission error could reduce by up to 33%. Further, ABI was able to detect 6-22% and 31-42% more ground-recorded fires than VIIRS in Georgia and Florida States, respectively, but ABI still missed many very small fires because ABI was hard to detect fires smaller than ~34.5 MW. Additionally, compared with 750-m VIIRS FRP, ABI FRP was ~30-50% larger in individual fire events but was overall similar at a regional scale.