LightAutoML
LightAutoML: A flexible open-source AutoML framework for tabular, text, and image workflows. Ranked #15 of 29 in AutoML Software by our editors (7.8/10); pricing: Open source; best for teams handling tabular, text, and image data.
At a glance
- Editor score7.8 / 10
- PricingOpen source
- Best forTeams handling tabular, text, and image data
- Paid fromFree
- Feature engineeringYes
- Facts checked21 Sep 2026

Where it wins
- Automates processing, feature selection, tuning, and model selection
- Supports tabular, text, and image workflows
- Includes reports, blending, and SHAP-based interpretation
Where it doesn't
- Requires Python development skills rather than a purely visual workflow
- The GitHub repository is marked Public archive
- Deployment and integration details are limited
Our verdict on LightAutoML
LightAutoML is an open-source Python framework for automated machine learning, aimed at Python developers, data engineers, data scientists, and researchers. It is suited to teams working with tabular, text, and image data that want automation without giving up the ability to construct custom pipelines. Presets cover common classification and regression workflows, while the framework also supports modular pipeline construction for more tailored projects. The listed platforms are web, Windows, macOS, and Linux.
Its strongest area is the breadth of automation within the modeling workflow. LightAutoML can handle data processing and feature typing, automatic feature selection, hyperparameter tuning, model comparison, blending, and best-model selection. It also generates reports and provides feature-importance and SHAP-based interpretation. That combination gives teams a way to move from prepared data to evaluated and interpreted models while retaining control over pipeline design. The published category specifications identify both automated model selection and model explainability, with workflow support described as both interface types.
LightAutoML is a better fit for technically capable teams than for buyers seeking a standalone, no-code product. Vendor materials describe a no-code version through SberCloud ML Space, but the core product is a Python framework. The GitHub repository is marked Public archive, while the vendor product page and documentation remain available. Choose LightAutoML when open-source access, automated modeling, custom pipelines, and support for multiple data types matter most. Consider an alternative when verified deployment details, integrations, or a fully managed workflow are central requirements.
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LightAutoML pricing
LightAutoML fact sheet
| Free plan | Not verified |
|---|---|
| Paid from | Free |
| Feature engineering | Yes |
| Automated model selection | Yes |
| Model explainability | Yes |
| Deployment options | Not verified |
| Workflow interface | Both |
| Hosting model | Both |
| Deployment | Cloud, Self-hosted |
| Platforms | Web, Windows, macOS, Linux |
| Support | Community, Docs |
| Built for | Solo, Small business, Mid-market, Enterprise (editorial estimate) |
| Pricing | Open source |
| Website | lightautoml.readthedocs.io |
| Facts checked | 21 Sep 2026 |
Alternatives to LightAutoML
- SAS ViyaA broad, governed AutoML platform for complex enterprise and regulated workloads.9.3
- DataRobotA focused enterprise AutoML platform with forecasting, deployment, monitoring, and governance.9.1
- IBM Watson StudioA broad AutoML workspace for teams that need collaboration, deployment and governance.9.0
See all LightAutoML alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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