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Horovod

Free#20 of 35 in Deep Learning Software

Horovod: Horovod adds multi-host, multi-GPU training to supported deep learning frameworks. Ranked #20 of 35 in Deep Learning Software by our editors (5.5/10); pricing: Free plan; best for teams adding multi-host training to existing frameworks.

5.5/10Editor score
Horovod5.5 Visit Horovod

At a glance

  • Editor score
    5.5 / 10
  • Pricing
    Free plan
  • Best for
    Teams adding multi-host training to existing frameworks
  • Free plan
    Yes
  • Paid from
    None
  • Training mode
    Both
  • Facts checked
    23 Sep 2026
  • Where it wins

    • Coordinates distributed training across multiple GPUs and hosts.
    • Supports TensorFlow, Keras, PyTorch, and Apache MXNet.
    • Provides collective operations and an elastic, fault-tolerant API via Gloo.
  • Where it doesn't

    • Windows is unsupported; installation is listed for Linux and macOS.
    • Its role focuses on coordinating distributed training, not a broader deep learning suite.
    • Support is through community channels and documentation.

Our verdict on Horovod

Horovod is an open-source framework for scaling deep learning training across multiple GPUs and hosts. It is aimed at teams with existing TensorFlow, Keras, PyTorch, or Apache MXNet training scripts that need to coordinate workers and average gradients across machines. The project is hosted by the LF AI & Data Foundation, and its published platform support covers Linux and macOS, with cloud and self-hosted deployment options. It is a focused addition to a training workflow rather than a general-purpose deep learning environment.

Its main strength is framework and operations breadth within that focused role. Horovod supports collective tensor operations including allreduce, allgather, broadcast, and alltoall, and distributed optimizers for gradient averaging. GPU operations use NCCL on CUDA or ROCm GPUs; MPI and Gloo coordinate workers. An elastic, fault-tolerant API is available via Gloo, and Apache Spark is also supported. These options make it relevant to teams choosing among existing frameworks and distributed execution setups, rather than requiring one framework-specific approach.

Horovod is presented as open-source software, so the product is available without a paid plan structure. The trade-off is scope: it helps scale training, but the supplied description does not position it as a broader platform for the full deep learning lifecycle. Installation is listed for Linux and macOS, and Windows is explicitly unsupported. Support channels are community and documentation. Teams seeking multi-host training across supported frameworks may find the scope appropriate; those needing Windows support or a more comprehensive deep learning environment should consider another tool.

Horovod pricing

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

Horovod fact sheet

Free planYes
Paid fromNone
Training modeBoth
Deployment targetsMultiple
GPU accelerationYes
Distributed trainingYes
Supported languagesPython
Model formatsNot verified
DeploymentCloud, Self-hosted
PlatformsLinux, macOS
SupportCommunity, Docs
Built forSmall business, Mid-market, Enterprise (editorial estimate)
Integrations8 integrations: TensorFlow, Keras, PyTorch, Apache MXNet, Apache Spark, MPI …
PricingFree plan
Websitehorovod.ai
Facts checked23 Sep 2026

Horovod integrations

Horovod lists 8 integrations on its own site.

  • TensorFlow
  • Keras
  • PyTorch
  • Apache MXNet
  • Apache Spark
  • MPI
  • Gloo
  • NCCL

Alternatives to Horovod

See all Horovod alternatives →

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Featured on iTechGuides

Featured on iTechGuides — Horovod 5.5/10

Horovod is listed in our Deep Learning Software directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026

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