Home/Compare/horovod vs accelerate

Comparison

horovod vs accelerate

Verdict

Pick horovod if simplify distributed deep learning training for TensorFlow, Keras, PyTorch, and MXNet with minimal code changes; pick accelerate if tool: accelerate.

Markdown twin · horovod alternatives · accelerate alternatives

GraphCanon updated 3w

horovod logo

horovod

horovod/horovod

15kpushed Jul 29, 2026
vs
accelerate logo

accelerate

huggingface/accelerate

9.8kpushed Jul 30, 2026

Trust & integrity

Signalhorovodaccelerate
Maintenance
Archived (4d since push)
As of 3w · github_public_v1
Very active (3d since push)
As of 3w · github_public_v1
Provenance
Not a fork · Organization account
As of 3w · github_public_v1
Not a fork · Organization account
As of 3w · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · osv@v1
deps.dev advisories
No lockfile (source not queried)
As of 3w · deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Published findings
As of 1mo · openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

horovod
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
accelerate
A tool for launching, training, and using PyTorch models with ease on various devices, configurations, including mixed precision support.

Stars

horovod
15k
accelerate
9.8k

Forks

horovod
2.2k
accelerate
1.4k

Open issues

horovod
406
accelerate
105

Language

horovod
Python
accelerate
Python

Adopt for

horovod
Simplify distributed deep learning training for TensorFlow, Keras, PyTorch, and MXNet with minimal code changes.
accelerate
Tool: accelerate

Persona

horovod
-
accelerate
-

Runtime

horovod
-
accelerate
-

License

horovod
Other
accelerate
Apache-2.0

Last pushed

horovod
Jul 29, 2026
accelerate
Jul 30, 2026

Categories

horovod
Model Training
accelerate
Inference & Serving, Model Training

Trust and health

Maintenance

horovod
Archived (8%)
accelerate
Very active (96%)

Days since push

horovod
4d
accelerate
3d

Archived on GitHub

horovod
Yes
accelerate
No

Open issues (now)

horovod
406
accelerate
105

deps.dev advisories

horovod
No lockfile (source not queried)
accelerate
Not queried

OpenSSF Scorecard

horovod
Published findings
accelerate
Not queried

Full report

accelerate
Trust report

Choose horovod if…

  • License: horovod is Other, accelerate is Apache-2.0.
  • Tags unique to horovod: deep-learning, distributed-training, keras, mxnet.
  • When you need to scale your training across multiple GPUs or nodes with little modification to existing scripts.

When NOT to use horovod

  • Avoid when extensive customization beyond core training is needed, as Horovod simplifies processes which might limit flexibility.
  • Not recommended if your project relies heavily on specific features not well-supported in Horovod's integration with frameworks like TensorFlow or PyTorch.

Choose accelerate if…

  • License: accelerate is Apache-2.0, horovod is Other.
  • Tags unique to accelerate: deepspeed, fsdp, mixed precision.
  • Also covers Inference & Serving.
  • Easy mixed-precision support for PyTorch models

When NOT to use accelerate

  • Non-PyTorch projects do not benefit from this tool
  • Doesnt offer advanced auto-tuning features for other frameworks like TensorFlow
  • Limited to Python environments compatible with PyTorch 1.10.0+

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: horovod 15k · accelerate 9.8k (synced Aug 3, 2026).

Common questions

What is the difference between horovod and accelerate?
horovod: Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.. accelerate: A tool for launching, training, and using PyTorch models with ease on various devices, configurations, including mixed precision support.. See the comparison table for live GitHub stats and shared categories.
When should I choose horovod over accelerate?
Choose horovod over accelerate when License: horovod is Other, accelerate is Apache-2.0; Tags unique to horovod: deep-learning, distributed-training, keras, mxnet; When you need to scale your training across multiple GPUs or nodes with little modification to existing scripts.
When should I choose accelerate over horovod?
Choose accelerate over horovod when License: accelerate is Apache-2.0, horovod is Other; Tags unique to accelerate: deepspeed, fsdp, mixed precision; Also covers Inference & Serving; Easy mixed-precision support for PyTorch models.
When should I avoid horovod?
Avoid when extensive customization beyond core training is needed, as Horovod simplifies processes which might limit flexibility. Not recommended if your project relies heavily on specific features not well-supported in Horovod's integration with frameworks like TensorFlow or PyTorch.
When should I avoid accelerate?
Non-PyTorch projects do not benefit from this tool Doesnt offer advanced auto-tuning features for other frameworks like TensorFlow Limited to Python environments compatible with PyTorch 1.10.0+
Is horovod or accelerate more popular on GitHub?
horovod has more GitHub stars (14,695 vs 9,803). Stars measure visibility, not whether either tool fits your constraints.
Are horovod and accelerate open source?
Yes - both are open-source projects on GitHub (horovod: Other, accelerate: Apache-2.0).
Where can I find alternatives to horovod or accelerate?
GraphCanon lists graph-backed alternatives at horovod alternatives and accelerate alternatives (horovod markdown twin, accelerate markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, horovod or accelerate?
horovod: Archived. accelerate: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for horovod and accelerate?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: horovod trust report; accelerate trust report.

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