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AI · head to head

AutoGen vs Keras

AutoGen logo

AutoGen

AI

Programming framework for multi-agent agentic AI

From
Free
Rated
-
Full reviewWebsite
Keras logo

Keras

Machine Learning

Deep learning API for humans

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: AutoGen framework now in maintenance mode, no new features planned; Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
  • They diverge on capability: AutoGen covers Multi-agent orchestration, 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 AutoGen and Keras actually diverge.

Attributes where AutoGen and Keras differ
AttributeAutoGenKeras
Pricing modelOpen source, no pricingopen-source
PlatformsPython, .NETPython, 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 AutoGen

  • Multi-agent orchestration
  • Message passing API
  • AgentChat API
  • Extensions API
  • MCP server support
  • AutoGen Studio
  • Cross-language support
  • Observable agent networks

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.

AutoGen

  • Building multi-agent conversational systemsnot Keras
  • Rapid prototyping of agent applicationsnot Keras
  • Research on agentic AI patterns and architecturesnot Keras
  • Distributed agent networks across boundariesnot Keras

Keras

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

Where each one falls short

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

AutoGen

  • Framework now in maintenance mode, no new features planned
  • Steeper learning curve for advanced use cases
  • Microsoft recommends new projects use Agent Framework instead
  • Limited to Python and .NET platforms

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

AutoGen

Free
  • Open SourceFree
    • MIT and CC-BY-4.0 licenses
    • Full framework access
    • Community support

Keras

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

Which should you pick?

Choose AutoGen if

  • You need multi-agent orchestration.
  • You want to start without paying.
  • You work on Python, .NET.
  • You also want message passing api.
AutoGen 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 AutoGen or Keras better?
Neither clearly leads. AutoGen 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, AutoGen or Keras?
AutoGen starts at Free and Keras at Free.
Does AutoGen or Keras run on more platforms?
AutoGen runs on Python, .NET. Keras runs on Python, Google Colab, Jupyter.
Can I use AutoGen for free?
Both have a free tier, so you can try either at no cost before committing.
What is AutoGen best used for?
AutoGen is most often used for building multi-agent conversational systems, rapid prototyping of agent applications, research on agentic ai patterns and architectures, distributed agent networks across boundaries. Of those, building multi-agent conversational systems and rapid prototyping of agent applications are not what Keras is typically brought in for.
What can AutoGen do that Keras cannot?
AutoGen covers Multi-agent orchestration, Message passing API, AgentChat API, Extensions API. Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning.

Answered from the vendors’ own pages

AutoGen: Is AutoGen still actively developed?

As of March 2026, AutoGen is in maintenance mode and will not receive new features. Microsoft recommends new projects use the Microsoft Agent Framework instead.

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
AutoGen: Can I still use AutoGen for new projects?

While AutoGen is stable and maintained for existing projects, Microsoft recommends using the Microsoft Agent Framework for new development.

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
AutoGen: What LLM providers does AutoGen support?

AutoGen includes extensions for OpenAI and Azure OpenAI through its Extensions API, with community support for other providers.

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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