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AI · head to head

Galileo vs Keras

Galileo logo

Galileo

AI

Evaluation and observability platform for GenAI applications and agents

From
Free
Free plan
Yes
Full reviewWebsite
Keras logo

Keras

Machine Learning

Deep learning API for humans

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Each has a real cost: Galileo the free plan is limited to 5,000 traces per month, which is quickly outgrown by production workloads.; Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
  • They diverge on capability: Galileo covers Pre-built evaluations, 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 Galileo and Keras actually diverge.

Attributes where Galileo and Keras differ
AttributeGalileoKeras
Pricing modelfreemiumopen-source
Platformsweb, apiPython, Google Colab, Jupyter
CategoryAIMachine Learning
FoundedUnknown2015

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 Galileo

  • Pre-built evaluations
  • Ground truth capture
  • Luna models
  • Agent behavior analysis
  • Production guardrails
  • Flexible deployment

Only in Keras

  • Sequential and Functional API
  • Pre-built neural network layers
  • Model training and evaluation
  • Transfer learning
  • Model serialization
  • TensorFlow
  • JAX
  • PyTorch

What people use each for

The jobs each tool is most often brought in to do.

Galileo

  • Evaluating RAG and agent applications before production releasenot Keras
  • Monitoring live GenAI applications for failures and driftnot Keras
  • Applying real-time guardrails without custom integration worknot Keras
  • Reducing evaluation costs using distilled Luna judge modelsnot Keras

Keras

  • Machine learningnot Galileo
  • Data analysisnot Galileo
  • Model trainingnot Galileo
  • Predictive analyticsnot Galileo

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Galileo

  • The free plan is limited to 5,000 traces per month, which is quickly outgrown by production workloads.
  • Real-time guardrails and unlimited trace capacity are reserved for the custom-priced Enterprise tier.
  • Pro plan pricing scales with trace volume, so costs can grow unpredictably as usage increases.
  • On-premises deployment requires an Enterprise contract rather than being available self-serve.

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

Galileo

Free
  • FreeFree
    • 5,000 traces/month
    • Unlimited users
    • Unlimited custom evaluations
  • Pro$100/month
    • 50,000 traces/month
    • Standard role-based access control
    • Advanced analytics and insights
  • Enterprise$undefined/mo
    • Unlimited trace capacity
    • Custom rate limits
    • Hosted, VPC, or on-prem deployment

Keras

Free
  • Open SourceFree
    • High-level API
    • Pre-built layers
    • Model serialization

Which should you pick?

Choose Galileo if

  • You need pre-built evaluations.
  • You want to start without paying.
  • You work on web, api.
  • You also want ground truth capture.
Galileo review

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.
Keras review

Questions people ask

Is Galileo or Keras better?
Neither clearly leads. Galileo 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, Galileo or Keras?
Galileo starts at Free and Keras at Free.
Does Galileo or Keras run on more platforms?
Galileo runs on web, api. Keras runs on Python, Google Colab, Jupyter.
Can I use Galileo for free?
Both have a free tier, so you can try either at no cost before committing.
What is Galileo best used for?
Galileo is most often used for evaluating rag and agent applications before production release, monitoring live genai applications for failures and drift, applying real-time guardrails without custom integration work, reducing evaluation costs using distilled luna judge models. Of those, evaluating rag and agent applications before production release and monitoring live genai applications for failures and drift are not what Keras is typically brought in for.
What can Galileo do that Keras cannot?
Galileo covers Pre-built evaluations, Ground truth capture, Luna models, Agent behavior analysis. Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning.

Answered from the vendors’ own pages

Galileo: What does Galileo cost?

Galileo offers a free plan, a Pro plan at $100/month billed yearly (with a 33% annual discount), and a custom-priced Enterprise plan for unlimited trace capacity.

Source
Keras: 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.

Source
Galileo: Is there a free plan, and what are its limits?

The Free plan includes 5,000 traces per month with unlimited users and unlimited custom evaluations, aimed at developers and small teams experimenting with GenAI.

Source
Keras: 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.

Source
Galileo: How is usage metered?

Galileo's pricing scales based on the number of traces processed each month, with Free capped at 5,000, Pro at 50,000, and Enterprise offering unlimited trace capacity.

Source
Keras: 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.

Source
Keras: 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.

Source
Keras: 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.

Source
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