Softwr

Machine Learning · head to head

Keras vs Ory Kratos

Keras logo

Keras

Machine Learning

Deep learning API for humans

From
Free
Rated
-
Ory Kratos logo

Ory Kratos

Cybersecurity

Headless identity and user management API

From
Free
Rated
-

The short version

  • Each has a real cost: Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs; Ory Kratos headless means you build every screen, which is significant work compared with a hosted login page
  • They diverge on capability: Keras covers Sequential and Functional API, Ory Kratos covers Headless API.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Keras and Ory Kratos actually diverge.

Attributes where Keras and Ory Kratos differ
AttributeKerasOry Kratos
Pricing modelopen-sourceOpen-source self-hosted, with a paid managed network
PlatformsPython, Google Colab, JupyterLinux, Docker, Kubernetes, Self-hosted
CategoryMachine LearningCybersecurity
Founded2015Unknown

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 Keras

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

Only in Ory Kratos

  • Headless API
  • Self-service flows
  • Multi-factor authentication
  • Pluggable identity schemas

What people use each for

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

Keras

  • Machine learningnot Ory Kratos
  • Data analysisnot Ory Kratos
  • Model trainingnot Ory Kratos
  • Predictive analyticsnot Ory Kratos

Ory Kratos

  • Products needing complete control over the look and flow of authenticationnot Keras
  • Applications that must not hand user identity data to a third partynot Keras
  • Teams building identity as infrastructure across several servicesnot Keras

Where each one falls short

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

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

Ory Kratos

  • Headless means you build every screen, which is significant work compared with a hosted login page
  • More moving parts than a monolithic IAM: Kratos handles identity, and OAuth2 needs Ory Hydra alongside
  • Documentation assumes real familiarity with identity concepts and is not a gentle introduction
  • Self-hosting identity carries the security and availability burden that hosted providers absorb

Pricing, plan by plan

Keras

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

Ory Kratos

Free
  • Self-hostedFree
    • Full identity server
    • All flows
    • Community support

Which should you pick?

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.

Choose Ory Kratos if

  • You need headless api.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want self-service flows.

Questions people ask

Is Keras or Ory Kratos better?
Neither clearly leads. Keras starts at Free and Ory Kratos at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Keras or Ory Kratos?
Keras starts at Free and Ory Kratos at Free.
Does Keras or Ory Kratos run on more platforms?
Keras runs on Python, Google Colab, Jupyter. Ory Kratos runs on Linux, Docker, Kubernetes, Self-hosted.
Can I use Keras for free?
Both have a free tier, so you can try either at no cost before committing.
What is Keras best used for?
Keras is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Ory Kratos is typically brought in for.
What can Keras do that Ory Kratos cannot?
Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. Ory Kratos covers Headless API, Self-service flows, Multi-factor authentication, Pluggable identity schemas.

Answered from the vendors’ own pages

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
Ory Kratos: Is Ory Kratos free?

Yes, open source and free to self-host. Ory Network is a paid managed service.

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
Ory Kratos: What does headless mean here?

Kratos provides identity flows as APIs and no user interface. You build the login, registration and recovery screens yourself.

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
Ory Kratos: Does Kratos do OAuth2?

No. Kratos handles user identity; OAuth2 and OpenID Connect provider functionality is Ory Hydra, a separate component.

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
Share

Related pages

Other head to heads