Machine Learning & Data Science · head to head
Comet ML vs Fathom

Comet ML
Machine Learning & Data Science
Platform for tracking, comparing, and optimizing ML experiments
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Comet ML the free cloud tier caps data at 25,000 spans a month with 60 day retention; Fathom team plan requires minimum 2 users; cannot purchase single seat at team pricing
- They diverge on capability: Comet ML covers Experiment tracking, Fathom covers Auto-recording.
Where they differ
Only the attributes on which Comet ML and Fathom actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Comet ML
- Experiment tracking
- Code versioning
- Model registry
- Hyperparameter optimization
- Production monitoring
- PyTorch
- TensorFlow
- Keras
Only in Fathom
- Auto-recording
- AI summaries
- Transcription
- Highlight clips
- Zoom
- Google Meet
- HubSpot
- Salesforce
Both cover
- Web support
What people use each for
The jobs each tool is most often brought in to do.
Comet ML
- Tracking machine learning experiments, metrics and model versionsnot Fathom
- Monitoring and evaluating LLM applications with tracingnot Fathom
Fathom
- AI-powered meeting transcription and automatic note-taking for sales teams and professionalsnot Comet ML
- Meeting analysis with AI scorecards and action item generation that syncs to CRMsnot Comet ML
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
Fathom
- Team plan requires minimum 2 users; cannot purchase single seat at team pricing
- CRM field sync and deal view summaries available only on Business plan ($34/user/month) and above
Pricing, plan by plan
Comet ML
Free- FreeFree
- 100 experiments
- Basic features
- Community support
- Team$179/month
- Unlimited experiments
- Team collaboration
- Priority support
Fathom
FreeNo published plan breakdown. See the Fathom review.
Which should you pick?
Choose Comet ML if
- You need experiment tracking.
- You want to start without paying.
- You work on Web, Linux, Mac, Windows.
- You also want code versioning.
Choose Fathom if
- You need auto-recording.
- You want to start without paying.
- You work on Web, Zoom, Google Meet, Microsoft Teams.
- You also want ai summaries.
Questions people ask
- Is Comet ML or Fathom better?
- Neither clearly leads. Comet ML starts at Free and Fathom at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Comet ML or Fathom?
- Comet ML starts at Free and Fathom at Free.
- Does Comet ML or Fathom run on more platforms?
- Comet ML runs on Web, Linux, Mac, Windows. Fathom runs on Web, Zoom, Google Meet, Microsoft Teams.
- Can I use Comet ML for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Comet ML best used for?
- Comet ML is most often used for tracking machine learning experiments, metrics and model versions, monitoring and evaluating llm applications with tracing. Of those, tracking machine learning experiments, metrics and model versions and monitoring and evaluating llm applications with tracing are not what Fathom is typically brought in for.
- What can Comet ML do that Fathom cannot?
- Comet ML covers Experiment tracking, Code versioning, Model registry, Hyperparameter optimization. Fathom covers Auto-recording, AI summaries, Transcription, Highlight clips. Both handle Web support.
Related pages
Other head to heads
- Comet ML vs AWS SageMaker
- Comet ML vs Google Vertex AI
- Comet ML vs Azure Machine Learning
- Comet ML vs DataRobot
- Comet ML vs Snowflake
- Comet ML vs TensorFlow
- Comet ML vs Keras
- Comet ML vs MLflow
- Comet ML vs Jupyter
- Comet ML vs PyTorch
- Comet ML vs scikit-learn
- Comet ML vs Apache Spark MLlib
- Comet ML vs Weights & Biases
- Comet ML vs Alteryx
- Comet ML vs Anaconda
- Comet ML vs Databricks
- Comet ML vs Dataiku
- Comet ML vs DVC
- Comet ML vs Pika
- Comet ML vs Anthropic API
- Comet ML vs D-ID
- Comet ML vs Stable Diffusion
- Comet ML vs AI21 Labs
- Comet ML vs ChatGPT
- Comet ML vs Copy.ai
- Comet ML vs HeyGen
- Comet ML vs Jasper
- Comet ML vs Leonardo AI
- Comet ML vs Murf
- Comet ML vs Perplexity
- Comet ML vs Pi
- Comet ML vs Play.ht
- Comet ML vs Replicate
- Comet ML vs Replika
- Comet ML vs Rytr
- Comet ML vs Together AI
- Fathom vs AWS SageMaker
- Fathom vs Google Vertex AI
- Fathom vs Azure Machine Learning
- Fathom vs DataRobot
- Fathom vs Snowflake
- Fathom vs TensorFlow
- Fathom vs Keras
- Fathom vs MLflow
- Fathom vs Jupyter
- Fathom vs PyTorch
- Fathom vs scikit-learn
- Fathom vs Apache Spark MLlib
- Fathom vs Weights & Biases
- Fathom vs Alteryx
- Fathom vs Anaconda
- Fathom vs Databricks
- Fathom vs Dataiku
- Fathom vs DVC
- Fathom vs Pika
- Fathom vs Anthropic API
- Fathom vs D-ID
- Fathom vs Stable Diffusion
- Fathom vs AI21 Labs
- Fathom vs ChatGPT
- Fathom vs Copy.ai
- Fathom vs HeyGen
- Fathom vs Jasper
- Fathom vs Leonardo AI
- Fathom vs Murf
- Fathom vs Perplexity
- Fathom vs Pi
- Fathom vs Play.ht
- Fathom vs Replicate
- Fathom vs Replika
- Fathom vs Rytr
- Fathom vs Together AI

