| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Windows | — | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 0 |
| Spec score · Deep Learning Software | 8.1 (#11) | 7.3 (#27) |
| Deployment | Horovod can be installed on-premise or run on AWS, Azure and Databricks. | The documentation describes deployment on cloud, servers, mobile and embedded devices, and ultra-lightweight devices such as earphones. |
| Open source | Horovod is described as an open source project hosted by the LF AI & Data Foundation. | Huawei announced that MindSpore became open source on Gitee on March 28, 2020. |
| Purpose | Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch and Apache MXNet. | MindSpore is an AI computing framework designed for AI application development across device, edge, and cloud scenarios. |
| Security | The documentation includes a security section for Horovod on Spark; the opened pages make no security certification or compliance claim. | MindSpore's documentation says its unified device-edge-cloud architecture addresses enterprise deployment and security challenges. |
| Support | The project directs users to documentation, troubleshooting guidance and a ticket submission link for unresolved issues. | The official site directs users to its forum for help and professional answers, and to AtomGit to submit issues. |