Comparison
horovod vs DeepLearningExamples
Verdict
Pick horovod if simplify distributed deep learning training for TensorFlow, Keras, PyTorch, and MXNet with minimal code changes; pick DeepLearningExamples if curated facts for DeepLearningExamples, tailored to its unique features and offerings.
Markdown twin · horovod alternatives · DeepLearningExamples alternatives
GraphCanon updated 1w
Trust & integrity
| Signal | horovod | DeepLearningExamples |
|---|---|---|
| Maintenance | Archived (4d since push) As of 3w · github_public_v1 | Dormant (734d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 1w · 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.
- DeepLearningExamples
- State-of-the-Art Deep Learning scripts for various applications
Stars
- horovod
- 15k
- DeepLearningExamples
- 15k
Forks
- horovod
- 2.2k
- DeepLearningExamples
- 3.4k
Open issues
- horovod
- 406
- DeepLearningExamples
- 321
Language
- horovod
- Python
- DeepLearningExamples
- Jupyter Notebook
Adopt for
- horovod
- Simplify distributed deep learning training for TensorFlow, Keras, PyTorch, and MXNet with minimal code changes.
- DeepLearningExamples
- Curated facts for DeepLearningExamples, tailored to its unique features and offerings.
Persona
- horovod
- -
- DeepLearningExamples
- -
Runtime
- horovod
- -
- DeepLearningExamples
- -
License
- horovod
- Other
- DeepLearningExamples
- -
Last pushed
- horovod
- Jul 29, 2026
- DeepLearningExamples
- Aug 12, 2024
Categories
- horovod
- Model Training
- DeepLearningExamples
- Inference & Serving, Model Training
Trust and health
Maintenance
- horovod
- Archived (8%)
- DeepLearningExamples
- Dormant (18%)
Days since push
- horovod
- 4d
- DeepLearningExamples
- 734d
Archived on GitHub
- horovod
- Yes
- DeepLearningExamples
- No
Open issues (now)
- horovod
- 406
- DeepLearningExamples
- 321
Stars delta
- horovod
- Unknown
- DeepLearningExamples
- +14 (30d)
Open issues delta
- horovod
- Unknown
- DeepLearningExamples
- -1 (30d)
deps.dev advisories
- horovod
- No lockfile (source not queried)
- DeepLearningExamples
- Not queried
OpenSSF Scorecard
- horovod
- Published findings
- DeepLearningExamples
- Not queried
Full report
- horovod
- Trust report
- DeepLearningExamples
- Trust report
Choose horovod if…
- horovod is primarily Python; DeepLearningExamples is Jupyter Notebook.
- Tags unique to horovod: distributed-training, keras, pytorch, tensorflow.
- 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 DeepLearningExamples if…
- DeepLearningExamples is primarily Jupyter Notebook; horovod is Python.
- Tags unique to DeepLearningExamples: computer-vision, drug-discovery, forecasting, large language models.
- Also covers Inference & Serving.
- The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance.
When NOT to use DeepLearningExamples
- Avoid using DeepLearningExamples if you do not have access to NVIDIA GPUs, as it is heavily optimized for these specific hardware configurations to provide maximum utilization of Tensor Cores.
- If your project requires frameworks that are less common (e.g., MXNet or PaddlePaddle) without the same level of support as PyTorch and TensorFlow on this platform, consider other repositories that n
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (horovod/horovod) · observed Aug 3, 2026
- GitHub forks (horovod/horovod) · observed Aug 3, 2026
- Last push (horovod/horovod) · observed Jul 29, 2026
- License file (Other) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (NVIDIA/DeepLearningExamples) · observed Aug 17, 2026
- GitHub forks (NVIDIA/DeepLearningExamples) · observed Aug 17, 2026
- Last push (NVIDIA/DeepLearningExamples) · observed Aug 12, 2024
- License file (unknown) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: horovod 15k · DeepLearningExamples 15k (synced Aug 3, 2026).
Common questions
- What is the difference between horovod and DeepLearningExamples?
- horovod: Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.. DeepLearningExamples: State-of-the-Art Deep Learning scripts for various applications. See the comparison table for live GitHub stats and shared categories.
- When should I choose horovod over DeepLearningExamples?
- Choose horovod over DeepLearningExamples when horovod is primarily Python; DeepLearningExamples is Jupyter Notebook; Tags unique to horovod: distributed-training, keras, pytorch, tensorflow; When you need to scale your training across multiple GPUs or nodes with little modification to existing scripts.
- When should I choose DeepLearningExamples over horovod?
- Choose DeepLearningExamples over horovod when DeepLearningExamples is primarily Jupyter Notebook; horovod is Python; Tags unique to DeepLearningExamples: computer-vision, drug-discovery, forecasting, large language models; Also covers Inference & Serving; The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance.
- 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 DeepLearningExamples?
- Avoid using DeepLearningExamples if you do not have access to NVIDIA GPUs, as it is heavily optimized for these specific hardware configurations to provide maximum utilization of Tensor Cores. If your project requires frameworks that are less common (e.g., MXNet or PaddlePaddle) without the same level of support as PyTorch and TensorFlow on this platform, consider other repositories that n
- Is horovod or DeepLearningExamples more popular on GitHub?
- DeepLearningExamples has more GitHub stars (14,844 vs 14,695). Stars measure visibility, not whether either tool fits your constraints.
- Are horovod and DeepLearningExamples open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to horovod or DeepLearningExamples?
- GraphCanon lists graph-backed alternatives at horovod alternatives and DeepLearningExamples alternatives (horovod markdown twin, DeepLearningExamples 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 DeepLearningExamples?
- horovod: Archived. DeepLearningExamples: Dormant. 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 DeepLearningExamples?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: horovod trust report; DeepLearningExamples trust report.