AI Infrastructure & MLOps Freemium

mlop

Open-source experiment tracking and lifecycle tools for machine learning

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PricingFreemium
Starting priceContact sales
Free planYes
Free trialYes
APIYes
Open sourceYes
DeploymentHybrid
Last verifiedJuly 30, 2026
Overview

Tool overview

mlop is listed under AI Infrastructure & MLOps AI tools.

Summary

What is mlop?

mlop is an open-source MLOps platform for tracking experiments, metrics, parameters, artifacts, media, prompts, and model-training runs. It offers a hosted service and self-hosting, with real-time visualization and workflow tools for individual engineers and teams.

Best fit

Best for

Machine-learning teams tracking and comparing experiments

Audience

Who is it for?

ML engineersData scientistsResearch teamsMLOps teamsAI startups
Recommendation

Decision note

Suitable for evaluation after confirming final commercial terms, permissions, data handling, and edit-screen aliases. Keep Needs Review enabled until a human verifies the published profile.

Capabilities

Key features

Tracks metrics, parameters, artifacts, and media

Visualizes training runs in real time

Supports hosted and self-hosted operation

Provides a Python SDK and command-line workflow

Offers Weights & Biases-compatible migration paths

Adds alerts, prompt analysis, and collaboration tools

Workflows

Use cases

Comparing machine-learning experiments

Monitoring model-training runs

Sharing results with an ML team

Migrating from another experiment tracker

Self-hosting experiment data

Strengths

Pros

  • Apache-2.0 open-source core
  • Free hosted tier with unlimited logging hours
  • Self-hosting is documented
  • Simple Python integration
Considerations

Limitations

mlop improves experiment visibility but does not validate model safety, data quality, reproducibility, or production suitability by itself. Teams should configure retention, access control, backups, model evaluation, and security before storing sensitive training data.

Cost

Pricing details

Pricing modelFreemium
Starting priceContact sales
Free planYes
Free trialYes
Pricing context

Billing options

Free tierContact salesCustom enterprise
Pricing context

Pricing note

Free costs $0 per month for one seat, unlimited logging hours, and 10 GB. Pro is contact-sales for up to ten seats and 100 GB. Enterprise adds unlimited seats and storage, self-hosting, audits, and founder support.

View official pricing
Compatibility

Supported languages

  • English
Connectivity

Integrations

PyTorch

PyTorch Lightning

Hugging Face Transformers

Weights & Biases

Specs

Technical details

PlatformsWeb
Multilingual supportUnknown
Login requiredYes
Open sourceYes
LicenseApache-2.0
DeploymentHybrid
Companymlop, inc.
Launch year2025
Current versionv0.0.1
Models / versionsmlop Python SDK
Editions / plansFree, Basic, Professional, Organization, and Custom plans
Data confidenceHigh
Last verifiedJuly 30, 2026
Documentation → Source code → Release notes → Data source →
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Answers

Frequently asked questions

mlop is an open-source MLOps platform for tracking experiments, metrics, parameters, artifacts, media, prompts, and model-training runs. It offers a hosted service and self-hosting, with real-time visualization and workflow tools for individual engineers and teams.
Machine-learning teams tracking and comparing experiments
The listed pricing model for mlop is Freemium. Pricing can change, so users should verify the latest plan details on the official website.
Yes. The current profile indicates that a free trial is available.
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