Machine Learning · head to head
Comet ML vs Keras
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; Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
- They diverge on capability: Comet ML covers Experiment tracking, Keras covers Sequential and Functional API.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Comet ML and Keras actually diverge.
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
- Keras
- scikit-learn
- Hugging Face
Only in Keras
- Sequential and Functional API
- Pre-built neural network layers
- Model training and evaluation
- Transfer learning
- Model serialization
- JAX
Both cover
- PyTorch
- TensorFlow
- Linux support
- Mac support
- Windows support
What people use each for
The jobs each tool is most often brought in to do.
Comet ML
- LLM observability and monitoringnot Keras
- AI agent testing and debuggingnot Keras
- Experiment tracking for machine learningnot Keras
- Model registry and version managementnot Keras
- ML model training monitoringnot Keras
Keras
- Machine learningnot Comet ML
- Data analysisnot Comet ML
- Model trainingnot Comet ML
- Predictive analyticsnot 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
Keras
- Limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
- Error messages can be vague and unhelpful, making debugging challenging
- Smaller ecosystem and fewer pre-trained models than TensorFlow or PyTorch
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
Keras
Free- Open SourceFree
- High-level API
- Pre-built layers
- Model serialization
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 Keras if
- You need sequential and functional api.
- You want to start without paying.
- You work on Python, Google Colab, Jupyter.
- You also want pre-built neural network layers.
Questions people ask
- Is Comet ML or Keras better?
- Neither clearly leads. Comet ML starts at Free and Keras at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Comet ML or Keras?
- Comet ML starts at Free and Keras at Free.
- Does Comet ML or Keras run on more platforms?
- Comet ML runs on Web, Linux, Mac, Windows. Keras runs on Python, Google Colab, Jupyter.
- 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 Keras is typically brought in for.
- What can Comet ML do that Keras cannot?
- Comet ML covers Experiment tracking, Code versioning, Model registry, Hyperparameter optimization. Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. Both handle PyTorch, TensorFlow, Linux support, Mac 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.
SourceKeras: What is Keras?
Keras is a high-level deep learning API built on top of TensorFlow that simplifies building and training neural networks. Keras 3 supports multiple backends including TensorFlow, PyTorch, and JAX, making it backend-agnostic.
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.
SourceKeras: What model architectures does Keras support?
Keras supports the Sequential model for linear stacks of layers, the Functional API for arbitrary graph architectures, and model subclassing for custom implementations. All approaches provide access to layers, optimizers, metrics, and callbacks.
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.
SourceKeras: Can Keras models run on TPUs and GPUs?
Yes, Keras models can run on TPU Pods or large GPU clusters, be exported to run in browsers or on mobile devices, and be served via web APIs.
SourceComet ML: Does Comet.ml offer academic pricing?
Yes, a free Pro plan is available for academic users; verification is required via signup.
SourceKeras: Does Keras offer pre-trained models?
Yes, Keras provides pre-trained models through KerasHub and Keras Applications for common deep learning tasks like image classification, object detection, and NLP.
SourceKeras: Who should use Keras?
Keras is ideal for beginners and rapid prototyping due to its simplicity and user-friendly interface. Advanced users and production deployments may benefit more from lower-level frameworks like TensorFlow or PyTorch for greater customization.
SourceRelated pages
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