| Mar 2020 | ResNet50-v1.5 Apsara AI Acceleration(AIACC) team in Alibaba Cloud source | 0:02:38 | $14.42 | 93.04% | 16 ecs.gn6e-c12g1.24xlarge (AlibabaCloud) | AIACC-Training 1.3 + Tensorflow 2.1 |
| May 2019 | ResNet-50 ModelArts Service of Huawei Cloud source | 0:02:43 | N/A | 93.10% | 16 nodes with InfiniBand (8*V100 with NVLink for each node) | Moxing v1.13.0 + TensorFlow v1.13.1 |
| Dec 2018 | ResNet-50 ModelArts Service of Huawei Cloud source | 0:09:22 | N/A | 93.23% | 16 * 8 * Tesla-V100(ModelArts Service) | Huawei Optimized MXNet |
| Sep 2018 | ResNet-50 fast.ai/DIUx (Yaroslav Bulatov, Andrew Shaw, Jeremy Howard) source | 0:18:06 | $118.07 | 93.11% | 16 p3.16xlarge (AWS) | PyTorch 0.4.1 |
| Sep 2018 | Resnet 50 Andrew Shaw, Yaroslav Bulatov, Jeremy Howard source | 0:18:53 | $61.63 | 93.19% | 64 * V100 (8 machines - AWS p3.16xlarge) | ncluster / Pytorch 0.5.0a0+0e8088d |
| Mar 2020 | ResNet50-v1.5 Apsara AI Acceleration(AIACC) team in Alibaba Cloud source | 0:21:38 | $7.43 | 93.05% | 1 ecs.gn6e-c12g1.24xlarge (AlibabaCloud) | AIACC-Training 1.3 + Tensorflow 2.1 |
| Aug 2019 | Resnet 50 ZTE AI Platform source | 0:23:11 | N/A | 93.03% | 8 nodes with InfiniBand (8*P100 for each node) | TensorFlow v1.12.0 |
| Sep 2018 | Resnet 50 Andrew Shaw, Yaroslav Bulatov, Jeremy Howard source | 0:29:43 | $48.48 | 93.02% | 32 * V100 (4 machines - AWS p3.16xlarge) | ncluster / Pytorch 0.5.0a0+0e8088d |
| Apr 2018 | ResNet50 Google source | 0:30:43 | N/A | 93.03% | Half of a TPUv2 Pod | TensorFlow 1.8.0-rc1 |
| Apr 2018 | AmoebaNet-D N6F256 Google source | 1:06:32 | N/A | 93.03% | 1/4 of a TPUv2 Pod | TensorFlow 1.8.0-rc1 |
| Apr 2019 | ResNet50 Setu Chokshi (MS AI MVP | PropertyGuru) source | 1:42:23 | $20.89 | 93.02% | Azure ND40s_v2 | PyTorch 1.0 |
| Feb 2019 | Resnet 50 v1 GE Healthcare (Min Zhang) source | 1:44:34 | $42.66 | 93.24% | 8*V100 (single p3.16xlarge) | tensorflow 1.11 + horovod |
| Apr 2018 | AmoebaNet-D N6F256 Google source | 1:58:24 | N/A | 93.17% | 1/16 of a TPUv2 Pod | TensorFlow 1.8.0-rc1 |
| Sep 2018 | ResNet50 Google Cloud TPU source | 2:44:31 | $12.60 | 93.34% | GCP n1-standard-2, Cloud TPU | TensorFlow v1.11.0 |
| Apr 2018 | Resnet 50 fast.ai + students team: Jeremy Howard, Andrew Shaw, Brett Koonce, Sylvain Gugger source | 2:57:28 | $72.40 | 93.05% | 8 * V100 (AWS p3.16xlarge) | fastai / pytorch |
| Apr 2018 | ResNet50 Intel(R) Corporation source | 3:25:55 | N/A | 93.02% | 128 nodes with Xeon Platinum 8124M / 144 GB / 36 Cores (Amazon EC2 [c5.18xlarge]) | Intel(R) Optimized Caffe |
| Apr 2018 | ResNet56 Intel(R) Corporation source | 3:31:47 | N/A | 93.11% | 128 nodes with Xeon Platinum 8124M / 144 GB / 36 Cores (Amazon EC2 [c5.18xlarge]) | Intel(R) Optimized Caffe |
| Sep 2018 | ResNet50 Google Cloud TPU source | 5:52:31 | $27.00 | 93.36% | GCP n1-standard-2, Cloud TPU | TensorFlow v1.11.0 |
| Apr 2018 | ResNet50 Intel(R) Corporation source | 6:09:50 | N/A | 93.05% | 64 nodes with Xeon Platinum 8124M / 144 GB / 36 Cores (Amazon EC2 [c5.18xlarge]) | Intel(R) Optimized Caffe |
| Apr 2018 | AmoebaNet-D N6F256 Google Cloud TPU source | 7:28:30 | $49.30 | 93.11% | GCP n1-standard-2, Cloud TPU | TensorFlow 1.8.0-rc0 |
| Apr 2018 | ResNet50 Google Cloud TPU source | 8:52:33 | $58.53 | 93.11% | GCP n1-standard-2, Cloud TPU | TensorFlow v1.8rc1 |
| Mar 2018 | ResNet50 Google Cloud TPU source | 12:26:39 | $82.07 | 93.15% | GCP n1-standard-2, Cloud TPU | TensorFlow v1.7rc1 |
| Aug 2019 | Resnet 50 Chuan Li source | 12:39:49 | $19.00 | 93.05% | Lambda GPU Cloud - 4x GTX 1080 Ti | ncluster / Pytorch 1.0.0 |
| Jan 2018 | ResNet50 DIUX source | 14:37:59 | $358.22 | 93.07% | p3.16xlarge | tensorflow 1.5, tensorpack 0.8.1 |
| Dec 2017 | ResNet152 ppwwyyxx source | 1 day, 20:28:27 | N/A | 93.94% | 8 P100 / 512 GB / 40 CPU (NVIDIA DGX-1) | tensorpack 0.8.0 |
| Oct 2017 | ResNet152 Stanford DAWN source | 10 days, 3:59:59 | $1112.64 | 93.00% | 8 K80 / 488 GB / 32 CPU (Amazon EC2 [p2.8xlarge]) | MXNet 0.11.0 |
| Oct 2017 | ResNet152 Stanford DAWN source | 13 days, 10:41:37 | $2323.39 | 93.38% | 4 M60 / 488 GB / 64 CPU (Amazon EC2 [g3.16xlarge]) | TensorFlow v1.3 |
