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Machine Learning · head to head

Keras vs Quadratic

Keras logo

Keras

Machine Learning

Deep learning API for humans

From
Free
Rated
-
Full reviewWebsite
Quadratic logo

Quadratic

Spreadsheets

Infinite-canvas spreadsheet that runs Python, SQL and formulas in the same grid

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; Quadratic aI usage is metered as a dollar allowance rather than a flat entitlement, so a team that adopts the agent enthusiastically will exhaust 20 USD per user per month quickly and the true cost per seat becomes unpredictable.
  • They diverge on capability: Keras covers Sequential and Functional API, Quadratic covers Multi-language cells.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Keras and Quadratic actually diverge.

Attributes where Keras and Quadratic differ
AttributeKerasQuadratic
Pricing modelopen-sourcePer user per month
PlatformsPython, Google Colab, JupyterWeb, macOS, Windows, Linux
CategoryMachine LearningSpreadsheets
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 Quadratic

  • Multi-language cells
  • Infinite canvas
  • Direct database connections
  • AI agent in the sheet
  • WebAssembly engine
  • Python package support

What people use each for

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

Keras

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

Quadratic

  • An analyst who wants a SQL result, a Python transformation and a set of manual assumptions visible in one file instead of three toolsnot Keras
  • Ad hoc modelling where part of the logic is genuinely code and part is a judgement call typed into a cellnot Keras
  • Sharing a reproducible analysis with a colleague who will only ever open a spreadsheet, not a notebooknot Keras
  • Prototyping a data pull against a warehouse before committing it to a scheduled pipelinenot 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

Quadratic

  • AI usage is metered as a dollar allowance rather than a flat entitlement, so a team that adopts the agent enthusiastically will exhaust 20 USD per user per month quickly and the true cost per seat becomes unpredictable.
  • Self-hosting is available only on the Enterprise plan, so an organisation that cannot send data to the vendor cloud has to enter a sales negotiation rather than run a container.
  • Excel and Google Sheets compatibility is partial, so files with heavy conditional formatting, pivot tables or macros do not survive a round trip and have to be rebuilt.
  • The product is young and the connector list is short, covering the main relational databases and two warehouses, so anything else has to be reached through Python code you write and maintain yourself.
  • There is no real mobile editing experience, which matters more than it sounds for a spreadsheet because approvals and quick checks routinely happen on a phone.

Pricing, plan by plan

Keras

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

Quadratic

Free
  • PersonalFree
    • Limited AI usage
    • Limited files and connections
    • Limited sharing
  • Pro$18/month
    • Billed annually
    • 20 USD of AI credits per month
    • Unlimited files
  • Business$36/month
    • Billed annually
    • 40 USD of AI credits per month
    • Advanced permissions
  • Enterprise$undefined/year
    • Quoted
    • Self-hosting option
    • Custom AI usage

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 Quadratic if

  • You need multi-language cells.
  • You want to start without paying.
  • You work on Web, macOS, Windows, Linux.
  • You also want infinite canvas.
Quadratic review

Questions people ask

Is Keras or Quadratic better?
Neither clearly leads. Keras starts at Free and Quadratic at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Keras or Quadratic?
Keras starts at Free and Quadratic at Free.
Does Keras or Quadratic run on more platforms?
Keras runs on Python, Google Colab, Jupyter. Quadratic runs on Web, macOS, Windows, Linux.
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 Quadratic is typically brought in for.
What can Keras do that Quadratic cannot?
Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. Quadratic covers Multi-language cells, Infinite canvas, Direct database connections, AI agent in the sheet.

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
Quadratic: Do I need to know Python to use it?

No, formulas work on their own, but the reason to choose Quadratic over Google Sheets is the code cells, so a team with no Python will not get the value.

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
Quadratic: What happens when the AI credits run out?

Prompting stops until the next monthly reset or until you move up a plan; the spreadsheet itself keeps working normally.

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
Quadratic: Can it replace a BI tool?

Not for scheduled distribution or governed metrics. It is for exploratory work by one person or a small team, not for dashboards a hundred people read.

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
Quadratic: Is my database query sent to the vendor?

Connections run through the vendor service on all plans except Enterprise self-hosting, which is the option to take if that is unacceptable.

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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