Tech riderRev. 21 Sept 2026
  1. 1Runs onNot stated by the maker
  2. 2CostsNot stated by the maker
  3. 3Run comparisonYes
  4. 4Artifact trackingYes
  5. 5Deployment optionsself hosted
  6. 6API and SDK accessYes
4 lines stated Written from the maker's own pages: inria-thoth.github.io
The MLXP homepage

Overview

MLXP is ranked #26 of 37 in ML experiment tracking software on Specifiction.

Compared on ML experiment tracking software

Run comparison
Yesinria-thoth.github.io
Artifact tracking
Yesinria-thoth.github.io
Deployment options
self_hostedinria-thoth.github.io
API and SDK access
Yesinria-thoth.github.io

Facts

Purpose
MLXP is an open-source Python framework for managing experiments from launching and logging through querying results.github.com · 4 Oct 2026
Job launching
It can launch several jobs automatically using Hydra and hierarchical configs, with a decorator on the main task function.github.com · 4 Oct 2026
Experiment records
It logs metrics, artifacts, checkpoints, metadata, and configuration options in a uniquely assigned job directory.github.com · 4 Oct 2026
Code versioning
It automatically generates a deployment version of the code based on the latest Git commit.github.com · 4 Oct 2026
Cluster jobs
It can submit jobs to a cluster using a job scheduler.github.com · 4 Oct 2026
Results
It supports reading, querying, grouping, and aggregating outputs from multiple jobs.github.com · 4 Oct 2026
Installation
The README says MLXP can be installed in a virtualenv or Conda environment with pip using `pip install MLXP`.github.com · 4 Oct 2026
Dependencies
The listed requirements include Hydra Core, OmegaConf, TinyDB, PyYAML, pandas, dill, and GitPython.github.com · 4 Oct 2026
License
The repository says MLXP is distributed under the MIT license.github.com · 4 Oct 2026
Documentation
The repository links to a quick start guide, a tutorial, and detailed documentation on the project website.github.com · 4 Oct 2026

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Sources