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Keras

Free#13 of 35 in Deep Learning Software

Keras: Free, open-source Keras gives Python teams one API across JAX, TensorFlow, and PyTorch. Ranked #13 of 35 in Deep Learning Software by our editors (6.1/10); pricing: Free plan; best for python teams wanting flexible framework backends.

6.1/10Editor score
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Keras6.1 Visit Keras

At a glance

  • Editor score
    6.1 / 10
  • Pricing
    Free plan
  • Best for
    Python teams wanting flexible framework backends
  • Free plan
    Yes
  • Paid from
    None
  • Training mode
    Local
  • Founded
    2015
  • Facts checked
    23 Sep 2026

  • Where it wins

    • Supports JAX, TensorFlow, and PyTorch backends
    • Exports models to .keras, ONNX, OpenVINO, LiteRT, and Torch formats
    • Provides pretrained models, distributed training, and mixed-precision policies

  • Where it doesn't

    • Self-hosted deployment requires teams to manage their own environments
    • Keras distribution API is currently implemented only for JAX
    • Python is the only supported language

Our verdict on Keras

Keras is an open-source deep learning framework for building, training, evaluating, and exporting neural-network models. It targets machine-learning developers and researchers working in computer vision, natural-language processing, audio, time-series, and generative AI. Models can use Sequential, Functional, or subclassed APIs, while built-in fit, evaluate, and predict methods cover common training workflows. Keras runs on Linux, macOS, and Windows, with local training and GPU support.

Keras is free software rather than a hosted commercial service, so teams deploy it in self-hosted environments. Its multi-backend design connects one high-level API to JAX, TensorFlow, or PyTorch, and supports mixed-framework pipelines using tf.data, PyTorch DataLoader, NumPy, and Pandas. KerasHub and KerasCV provide pretrained model implementations and checkpoints. The ecosystem also includes OpenVINO integration and export targets such as TensorFlow SavedModel, ONNX, OpenVINO, LiteRT, and PyTorch formats, giving teams options for inference workflows across platforms.

For larger workloads, Keras supports multi-device data and model parallelism, plus mixed-precision policies for GPU and TPU workloads. Its native .keras format saves full models, while export options help separate training from deployment. A notable constraint is that Keras's own distribution API is currently implemented only for the JAX backend; TensorFlow and PyTorch users rely on those frameworks' native distribution integrations. Python-only support and self-hosted operation make Keras a strong fit for Python teams that want backend choice and control, but less suitable for groups seeking another programming language or a managed hosted service.

Keras pricing

Plans Free planFree Free to use — no paid tier required for the core job.
See plans on keras.io

Keras fact sheet

Free planYes
Paid fromNone
Training modeLocal
Deployment targetsMultiple
GPU accelerationYes
Distributed trainingYes
Supported languagesPython
Model formatsKeras (.keras), TensorFlow SavedModel, ONNX, OpenVINO, LiteRT, PyTorch ExportedProgram
DeploymentSelf-hosted
PlatformsLinux, macOS, Windows
SupportCommunity, Docs
Built forSolo, Small business, Mid-market, Enterprise (editorial estimate)
Integrations4 integrations: JAX, TensorFlow, PyTorch, OpenVINO
PricingFree plan
Websitekeras.io
Facts checked23 Sep 2026

Keras integrations

Keras lists 4 integrations on its own site.

  • JAX
  • TensorFlow
  • PyTorch
  • OpenVINO

Alternatives to Keras

See all Keras alternatives →

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Featured on iTechGuides — Keras 6.1/10

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Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026

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