#43 in AI Development PlatformsUpdated 2026-08

mlop

by mlop · Open-source experiment tracking for machine learning teams

35.6 — BenchRank score out of 100

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Overview

mlop is an open-source platform for tracking machine learning experiments. A Python SDK logs metrics, parameters, gradients and images from a training run, alongside model versions, git commit and uncommitted files, and the web app charts them over time and sends email alerts on performance issues. The API is stated to be compatible with Weights & Biases.

Best for: ML teams wanting open-source experiment tracking that is API-compatible with Weights & Biases
Pricing: Free tier at $0/month for one seat with 10 GB storage; Pro and Enterprise prices are not published and require contacting the vendor.
Runs on: Web

Strengths and trade-offs

Strengths

Open source, with a self-hosted option on the Enterprise tier
States 100% compatibility with the Weights & Biases API
Logs parameters, gradients, media and git state per run
Free tier has unlimited logging hours and 10 GB storage

Trade-offs

Pro and Enterprise prices are not published; you must contact sales
Compute is in private beta and inference is listed as coming soon
Free tier is a single seat with 10 GB storage
Pro is capped at 10 seats and 100 GB storage

Pricing

Published plans from mlop’s own pricing page, in USD. Usage charges and add-ons may apply on top.

mlop pricing tiers, monthly rates in USD
Plan	Monthly	Includes
Free	Freeper month	1 team seat Unlimited logging hours 10 GB storage
Pro	Contact sales	Up to 10 team seats Unlimited logging hours 100 GB storage Email support
Enterprise	Contact sales	Unlimited seats, logging hours and storage 24/7 support from founders Self-hosted option and security audit Private Slack channel

How this score is made up

Each dimension is scored out of 100 and combined into the headline score using fixed weights.

MCP support: 0 out of 100
API quality: 10 out of 100
Documentation: 50 out of 100
Agent friendliness: 41 out of 100
Pricing transparency: 85 out of 100
Changelog: 25 out of 100
Marketing site structure: 95 out of 100
Operational trust: 0 out of 100

Measured, but not part of the score

Useful to know, but not a mark for or against the product — so these do not affect the ranking.

Openness: 85 out of 100
Maintenance: 65 out of 100

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