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Comet ML

Platform for tracking, comparing, and optimizing ML experiments

As of 30 August 2026, Comet ML has a free plan and paid plans start at $19/month. Comet ML is an experiment management platform that helps data scientists track, compare, explain, and optimize machine learning experiments. Softwr lists it under Machine Learning. Comet ML is launched in 2017, available on Web, Linux, macOS, Windows.

Overview

What Comet ML does

Comet ML is an experiment management platform that helps data scientists track, compare, explain, and optimize machine learning experiments. It provides automatic code versioning, hyperparameter tracking, and model management capabilities.

What people use it for

  • LLM observability and monitoring
  • AI agent testing and debugging
  • Experiment tracking for machine learning
  • Model registry and version management
  • ML model training monitoring

The honest half

Where it falls short

Concrete and checkable, so you can decide whether any of them matter to you. This is the half of a review a vendor will not write about Comet ML.

  • The free cloud tier caps data at 25,000 spans a month with 60 day retention
  • Retention stays at 60 days even on the paid Pro plan, and extending it is a $29 per 100k spans add on
  • Overage on Pro is $5 per additional 100,000 spans
  • The free MLOps tier is a single user with 100 GB of storage and training hours governed by a fair usage policy
  • Pro MLOps is $19 per user per month and caps the team at 10 users

Cross-shopped

What people choose instead of Comet ML

Each pairing was judged by two reviewers asking whether a buyer would genuinely weigh the two against each other. The ones that failed were deleted rather than published.

Pricing

What Comet ML costs

Taken from the vendor's own pricing page. Prices move, so check before you buy.

Free Cloud

Free

  • Up to 10 team members
  • 25,000 spans per month
  • 60-day data retention
  • AI observability and agent testing

Pro Cloud

$19 /mo

  • Up to 50 team members
  • 100,000 spans per month
  • 60-day data retention
  • Customizable span limits
  • Custom data retention periods

MLOps Free

Free

  • 1 user with fair usage policy
  • Experiment tracking
  • Dataset management
  • Model registry
  • LLM evaluation included

MLOps Pro

$19 /user/month

  • Up to 10 users
  • 1,500 training hours included
  • 500GB storage included
  • $1 per additional training hour
  • $3 per 100GB/month additional storage

Capabilities

Features

  • Experiment tracking

  • Code versioning

  • Model registry

  • Hyperparameter optimization

  • Production monitoring

  • PyTorch

    Integration with PyTorch

  • TensorFlow

    Integration with TensorFlow

  • Keras

    Integration with Keras

  • scikit-learn

    Integration with scikit-learn

  • Hugging Face

    Integration with Hugging Face

  • Web support

    Available on web

  • Linux support

    Available on linux

Answered, with sources

Questions people ask

Each answer names the page it came from, so you can check it rather than take our word for it.

Does Comet.ml offer a free plan?

Yes, Comet.ml offers free tiers for both Opik (cloud observability) and MLOps platforms. Free Cloud Opik includes up to 10 team members and 25,000 spans/month. Free MLOps tier is limited to 1 user.

Source
How many team members can use the free Comet.ml tier?

Free Cloud supports up to 10 team members. The Pro Cloud plan supports up to 50 team members at $19/month.

Source
What is a span in Comet.ml pricing?

A span represents a single tracked operation such as model requests or function calls. Free Cloud tier includes 25,000 spans per month.

Source
Does Comet.ml offer academic pricing?

Yes, a free Pro plan is available for academic users; verification is required via signup.

Source

Behind it

Who makes Comet ML

Company
Comet ML
Based in
New York, New York
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Softwr does not host reviews and shows no star rating for Comet ML, because a rating we did not collect is not ours to publish. What is here is the pricing and platform detail from the vendor’s own pages, limitations we could state concretely, and alternatives a reviewer confirmed people weigh against it. Tell us if any of it is wrong.

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