Shortening the scan time for acquiring an MR image is a major outstanding problem for the MRI community. To engage the community towards this objective, we hosted the second fastMRI competition for reconstructing MR images with subsampled k-space data. The data set for the 2020 competition focused on brain images and included 7,299 anonymized, fully-sampled brain scans, with 894 of these held back for challenge evaluation purposes. Our challenge included a qualitative evaluation component where radiologists assessed submissions for “quality of depiction of pathology.” Our challenge also introduced a Transfer track, where participants were asked to run their models on scanners from MRI manufacturers from outside the data set. Results showed one team scoring best in both SSIM scores and qualitative radiologist evaluations, establishing a new state-of-the-art for MRI acceleration.