Machine Learning · head to head
Comet ML vs Hugging Face

Comet ML
Machine Learning
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; Hugging Face model discovery across 3 million models lacks robust filtering and sorting by quality metrics
- They diverge on capability: Comet ML covers Experiment tracking, Hugging Face covers Model hub.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Comet ML and Hugging Face actually diverge.
| Attribute | Comet ML | Hugging Face |
|---|---|---|
| Pricing model | freemium | Unknown |
| Platforms | Web, Linux, Mac, Windows | Web, API |
| Founded | 2017 | 2016 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning).
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 Hugging Face
- Model hub
- Datasets
- Spaces
- Transformers library
- GitHub
- Cloud providers
- MLOps tools
- Api support
Both cover
- Web support
What people use each for
The jobs each tool is most often brought in to do.
Comet ML
- LLM observability and monitoringnot Hugging Face
- AI agent testing and debuggingnot Hugging Face
- Experiment tracking for machine learningnot Hugging Face
- Model registry and version managementnot Hugging Face
- ML model training monitoringnot Hugging Face
Hugging Face
- ai tools managementnot Comet ML
- Workflow automationnot Comet ML
- Reportingnot 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
Hugging Face
- Model discovery across 3 million models lacks robust filtering and sorting by quality metrics
- Community-driven content means variable model quality and documentation
- Private models and datasets require Pro subscription
- Enterprise support and SLAs require custom arrangements
Pricing, plan by plan
Comet ML
Free- Free CloudFree
- Up to 10 team members
- 25,000 spans per month
- 60-day data retention
- Pro Cloud$19/month
- Up to 50 team members
- 100,000 spans per month
- 60-day data retention
- MLOps FreeFree
- 1 user with fair usage policy
- Experiment tracking
- Dataset management
- MLOps Pro$19/user/month
- Up to 10 users
- 1,500 training hours included
- 500GB storage included
Hugging Face
FreeNo published plan breakdown. See the Hugging Face 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 Hugging Face if
- You need model hub.
- You want to start without paying.
- You work on Web, API.
- You also want datasets.
Questions people ask
- Is Comet ML or Hugging Face better?
- Neither clearly leads. Comet ML starts at Free and Hugging Face at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Comet ML or Hugging Face?
- Comet ML starts at Free and Hugging Face at Free.
- Does Comet ML or Hugging Face run on more platforms?
- Comet ML runs on Web, Linux, Mac, Windows. Hugging Face runs on Web, API.
- 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 llm observability and monitoring, ai agent testing and debugging, experiment tracking for machine learning, model registry and version management. Of those, llm observability and monitoring and ai agent testing and debugging are not what Hugging Face is typically brought in for.
- What can Comet ML do that Hugging Face cannot?
- Comet ML covers Experiment tracking, Code versioning, Model registry, Hyperparameter optimization. Hugging Face covers Model hub, Datasets, Spaces, Transformers library. Both handle Web support.
Answered from the vendors’ own pages
Comet ML: 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.
SourceHugging Face: Is Hugging Face free to use?
Yes. Hugging Face allows users to host and collaborate on unlimited public models, datasets, and applications at no cost. Models can be accessed and used freely from the Hub.
SourceComet ML: 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.
SourceHugging Face: How many models are available on Hugging Face?
Hugging Face Hub currently hosts nearly 3 million machine learning models across various tasks including text generation, image processing, and video generation.
SourceComet ML: 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.
SourceHugging Face: What is the Hugging Face Inference API?
Hugging Face provides access to 45,000+ models from leading AI providers through a single unified API with no service fees, simplifying access to diverse models.
SourceComet ML: Does Comet.ml offer academic pricing?
Yes, a free Pro plan is available for academic users; verification is required via signup.
SourceHugging Face: What content types does Hugging Face support?
Hugging Face supports text, image, video, audio, and 3D content models, allowing collaboration across multiple modalities and use cases.
SourceHugging Face: What is the transformers library?
Transformers is a Hugging Face library built for natural language processing applications, providing pre-built models and utilities for NLP tasks.
SourceRelated pages
More on Hugging Face
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