Software · head to head
Comet ML vs Looker

Comet ML
Software
Platform for tracking, comparing, and optimizing ML experiments
- From
- Free
- Rated
- -
The short version
- Only Comet ML has a free tier, so it costs nothing to try first.
- Each has a real cost: Comet ML the free cloud tier caps data at 25,000 spans a month with 60 day retention; Looker requires annual commitment with no month-to-month billing option
- They diverge on capability: Comet ML covers Experiment tracking, Looker covers LookML Data Modeling.
Where they differ
Only the attributes on which Comet ML and Looker actually diverge.
Identical on both: user rating (Not yet rated), category (Unknown).
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 Looker
- LookML Data Modeling
- Embedded Analytics
- API Access
- Version Control
- Data Actions
- BigQuery
- Snowflake
- Redshift
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 Looker
- Monitoring and evaluating LLM applications with tracingnot Looker
Looker
- Business intelligence and interactive dashboards for data-driven decision makingnot Comet ML
- Embedded analytics for integrating BI capabilities into third-party applicationsnot 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
Looker
- Requires annual commitment with no month-to-month billing option
- Conversational analytics will incur token overage charges ($3.00 per 1M input tokens, $20.00 per 1M output tokens) after October 1, 2026
Pricing, plan by plan
Comet ML
Free- FreeFree
- 100 experiments
- Basic features
- Community support
- Team$179/month
- Unlimited experiments
- Team collaboration
- Priority support
Looker
On requestNo published plan breakdown. See the Looker 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 Looker if
- You need lookml data modeling.
- You work on Web, Cloud (Google Cloud Platform).
- You also want embedded analytics.
Questions people ask
- Is Comet ML or Looker better?
- Neither clearly leads. Comet ML starts at Free and Looker at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Comet ML or Looker?
- Comet ML has a free tier; the other does not. Paid plans start at Free for Comet ML and On request for Looker.
- Does Comet ML or Looker run on more platforms?
- Comet ML runs on Web, Linux, Mac, Windows. Looker runs on Web, Cloud (Google Cloud Platform).
- Can I use Comet ML for free?
- Yes. Comet ML has a free tier, so you can try it without paying. Looker starts at On request.
- 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 Looker is typically brought in for.
- What can Comet ML do that Looker cannot?
- Comet ML covers Experiment tracking, Code versioning, Model registry, Hyperparameter optimization. Looker covers LookML Data Modeling, Embedded Analytics, API Access, Version Control. Both handle Web support.
Related pages
Keep looking
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 Tableau
- Comet ML vs Metabase
- Comet ML vs Redash
- Comet ML vs Fibery
- Comet ML vs Apache Superset
- Comet ML vs Baserow
- Comet ML vs Budibase
- Comet ML vs NocoDB
- Looker vs AWS SageMaker
- Looker vs Google Vertex AI
- Looker vs Azure Machine Learning
- Looker vs DataRobot
- Looker vs Snowflake
- Looker vs TensorFlow
- Looker vs Keras
- Looker vs MLflow
- Looker vs Jupyter
- Looker vs PyTorch
- Looker vs scikit-learn
- Looker vs Apache Spark MLlib
- Looker vs Weights & Biases
- Looker vs Alteryx
- Looker vs Anaconda
- Looker vs Databricks
- Looker vs Dataiku
- Looker vs DVC
- Looker vs Tableau
- Looker vs Metabase
- Looker vs Redash
- Looker vs Fibery
- Looker vs Apache Superset
- Looker vs Baserow
- Looker vs Budibase
- Looker vs NocoDB

