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Machine Learning · head to head

Keras vs Ory

Keras logo

Keras

Machine Learning

Deep learning API for humans

From
Free
Rated
-
Full reviewWebsite
Ory logo

Ory

Cybersecurity

Open-source identity, authentication, and permissions infrastructure

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs; Ory production and Growth plans are billed annually ($770/year and $9,350/year), which is a larger upfront commitment than monthly-only competitors.
  • They diverge on capability: Keras covers Sequential and Functional API, Ory covers Authentication APIs.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Keras and Ory actually diverge.

Attributes where Keras and Ory differ
AttributeKerasOry
Pricing modelopen-sourceusage-based
PlatformsPython, Google Colab, Jupyterweb, api
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

  • Authentication APIs
  • Permissions engine
  • Machine-to-machine tokens
  • B2B organizations
  • SAML SSO
  • Multi-region deployments

What people use each for

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

Keras

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

Ory

  • Adding self-hosted or cloud identity to a new productnot Keras
  • Implementing fine-grained permission checksnot Keras
  • Supporting B2B organizations and multi-tenancynot Keras
  • Building machine-to-machine authentication for microservicesnot 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

  • Production and Growth plans are billed annually ($770/year and $9,350/year), which is a larger upfront commitment than monthly-only competitors.
  • SAML SSO and multi-region deployments are reserved for the custom-priced Enterprise tier.
  • Usage-based pricing across aDAU, M2M tokens, and permission checks makes cost estimation more complex than flat per-MAU billing.

Pricing, plan by plan

Keras

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

Ory

Free
  • DeveloperFree
    • Community support
    • No production environments
  • Production$64/month
    • $21 monthly credit included
    • 1 production environment
    • 3 staging environments
  • Growth$779/month
    • $255 monthly credit included
    • 2 production environments
    • B2B organizations (max 3)

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.
Keras review

Choose Ory if

  • You need authentication apis.
  • You want to start without paying.
  • You work on web, api.
  • You also want permissions engine.
Ory review

Questions people ask

Is Keras or Ory better?
Neither clearly leads. Keras starts at Free and Ory at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Keras or Ory?
Keras starts at Free and Ory at Free.
Does Keras or Ory run on more platforms?
Keras runs on Python, Google Colab, Jupyter. Ory runs on web, api.
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 is typically brought in for.
What can Keras do that Ory cannot?
Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. Ory covers Authentication APIs, Permissions engine, Machine-to-machine tokens, B2B organizations.

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: What does Ory cost?

Ory has a free Developer tier, a Production plan at $770/year including a $21 monthly credit, a Growth plan at $9,350/year including a $255 monthly credit, and custom Enterprise pricing.

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
Ory: How is usage metered?

Beyond the included credit, Ory charges per average daily active user (aDAU), per machine-to-machine token, and per permission check, with lower per-unit rates on the Growth plan.

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
Ory: What payment methods are supported?

Ory accepts credit cards (Visa, MasterCard, Amex) and bank transfer, processed via Stripe.

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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