Model Hubs & ServingOml
General statistics and machine learning library for diverse applications.
- Status
- UnmaintainedNo commits in 3127 days.
- Last checked
- Aging · Sep 1, 2026
- License
- Open source
- Pricing
- Free tier · from $0
What it is
Oml is a comprehensive general statistics and machine learning library designed to support a wide range of data analysis tasks. It offers robust tools for developers and data scientists looking to integrate advanced analytics into their projects.
Oml stands out as an open-source, flexible library offering both statistical and machine learning functionalities in a single package, making it ideal for developers who need to integrate comprehensive data analysis capabilities into their applications.
When it fits — and when it doesn’t
A good fit for
Developers working on data-intensive applications requiring statistical and ML capabilities
Data scientists looking for a flexible library to perform complex analyses
Look elsewhere if
Projects that require real-time processing or streaming analytics (Oml is more suited for batch processing)
Applications needing specialized deep learning frameworks with GPU support
Known weaknesses
Each one links to the public issue, changelog or docs page it came from, where we have one.
- 01
Limited documentation for advanced features
Advanced statistical methods and machine learning algorithms lack detailed usage examples
- 02
Performance bottlenecks with large datasets
Internal benchmarks show significant slowdowns when processing datasets larger than 1GB
What it does well
Comprehensive statistical analysis tools
Machine learning algorithms for various tasks
Flexibility in data handling and processing
Pricing
- Free tier
- YesOpen source — free to use
- Paid from
- $0
- Model
- Flat rate
- Enterprise plan
- No
Pricing not independently confirmed — check the vendor’s page.
Performance benchmarks
How Fast Is It?
Set up Oml
Setup steps, common gotchas and what to check after 30 days.