H2O Driverless AI vs Paperspace Gradient
H2O Driverless AI
h2o.aiPaperspace Gradient
paperspace.comSide by side
| Figure | H2O Driverless AI | Paperspace Gradient |
|---|---|---|
| Price from | — | $8/mo |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 17 |
| Spec score · Data Science and Machine Learning Platforms | 7.8 (#8) | 8.7 (#3) |
| Intended users | H2O describes data scientists, DevOps and IT professionals, and business analysts as audiences for Driverless AI. | The pricing page describes plans for beginners and individual ML/AI engineers, data scientists, researchers, teams, research groups, and startups. |
| What it does | Driverless AI automates feature engineering, model building, visualization, and interpretability. | Paperspace is a cloud machine-learning platform for developing, training, and deploying AI applications with GPU-backed infrastructure. |
Plans
Paperspace Gradient
- Free (Individual)Free
- Pro (Individual)$8 a month
- Growth (Individual)$39 a month
- Free (Team)Free
- Pro (Team)$12 a month
- Growth (Team)$39 a month
- T0Free
- T1$12 a month
- FreeFree
- FreeFree
In their own words
H2O Driverless AI
H2O Driverless AI automates machine-learning work from feature engineering and model building through validation, tuning, selection, visualization, interpretability, and scoring-pipeline generation. It explains model output at both global and individual-prediction levels. Models can be deployed as REST endpoints, cloud services, or optimized Java code for edge devices. Supported hardware includes NVIDIA GPUs, IBM Power 9, and Intel x86 CPUs; GPU-accelerated algorithms include XGBoost, TensorFlow, and LightGBM. Documented integrations include Kubernetes, Kubeflow, SageMaker, Alteryx, Jupyter/Python, KDB, Qlik, Trifacta, and UiPath. Data sources include HDFS, Amazon S3, Azure Blob Storage, Google BigQuery, Google Cloud Storage, Snowflake, JDBC, Databricks, and Delta Table. Cloud installation options are H2O AI Cloud, AWS, Azure, and Google Cloud. H2O offers a 21-day public-cloud evaluation license and a guided two-hour cloud test drive. Commercial licensing requires contacting sales; no price is listed. The default installation disables security, so production use calls for secure installation.
Paperspace Gradient
Paperspace Gradient is a machine learning platform for building, tracking, and collaborating on models. Its browser-based IDE launches GPU-enabled Jupyter notebooks; teams can share projects, invite collaborators, and connect GitHub to manage code and compute resources. Notebook environments run in Docker containers. For deployment, Gradient serves models through API endpoints, with runtime, instance-type, and autoscaling choices. On-demand GPU and IPU instances are available, and paid instance utilization can cost extra beyond plan fees. Gradient supports major machine learning frameworks and libraries. Plans include free options and paid options listed from $8/mo; individual and team plans have different storage allowances, and notebook plans specify limits on notebooks and running sessions. Gradient is offered for beginners, ML/AI engineers, data scientists, researchers, teams, research groups, and startups. Paperspace also lists a Windows, macOS, and Linux beta desktop app, along with centralized permissions and activity logs.