Comparison
hub vs mesh
Verdict
Pick hub if hub is specifically tailored to Python developers who wish to incorporate transfer learning into their TensorFlow projects with pre-trained model components for applications such as image classification; pick mesh if mesh TensorFlow supports simplified model parallelism across multiple devices in Python under the Apache-2.0 license.
Markdown twin · hub alternatives · mesh alternatives
GraphCanon updated 2w
Trust & integrity
| Signal | hub | mesh |
|---|---|---|
| Maintenance | Dormant (551d since push) As of 1mo · github_public_v1 | Archived (993d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1mo · github_public_v1 | Not a fork · Organization account As of 2w · 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 | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- hub
- A library for transfer learning by reusing parts of TensorFlow models.
- mesh
- Mesh TensorFlow: Model Parallelism Made Easier
Stars
- hub
- 3.5k
- mesh
- 1.6k
Forks
- hub
- 1.6k
- mesh
- 255
Open issues
- hub
- 11
- mesh
- 98
Language
- hub
- Python
- mesh
- Python
Adopt for
- hub
- hub is specifically tailored to Python developers who wish to incorporate transfer learning into their TensorFlow projects with pre-trained model components for applications such as image classification.
- mesh
- Mesh TensorFlow supports simplified model parallelism across multiple devices in Python under the Apache-2.0 license.
Persona
- hub
- -
- mesh
- -
Runtime
- hub
- -
- mesh
- -
License
- hub
- hub is licensed under Apache-2.0, allowing for broad use in both open source and commercial projects.
- mesh
- Apache-2.0
Last pushed
- hub
- Jan 17, 2025
- mesh
- Nov 17, 2023
Categories
- hub
- Data & Retrieval, Model Training
- mesh
- Model Training
Trust and health
Maintenance
- hub
- Dormant (18%)
- mesh
- Archived (8%)
Days since push
- hub
- 551d
- mesh
- 993d
Archived on GitHub
- hub
- No
- mesh
- Yes
Open issues (now)
- hub
- 11
- mesh
- 98
Full report
- hub
- Trust report
- mesh
- Trust report
Choose hub if…
- Pricing: The core functionalities of hub are free to use with an open-source license; however, additional services or enterprise support might incur costs..
- Requirements: Requires a Python environment and TensorFlow installation to operate..
- Tags unique to hub: embeddings, image-classification, machine-learning, ml.
- Also covers Data & Retrieval.
- When you need to leverage existing TensorFlow models and integrate specific parts of them for tasks like embedding or image-classification without retraining the entire model from scratch.
When NOT to use hub
- When working strictly with non-TensorFlow frameworks such as PyTorch or MXNet, as hub is built specifically for enhancing and reusing models within TensorFlow.
- If your project requires a more generalized approach to machine-learning without reliance on pre-existing model components, focusing instead on training models from the ground up.
Choose mesh if…
- Tags unique to mesh: model parallelism.
- When working on large models that benefit from being split across many devices.
When NOT to use mesh
- If you are looking for a tool that simplifies other aspects of machine learning beyond model-parallel computation.
- For projects with limited GPU/TPU resources where multi-device parallelism is not required.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (tensorflow/hub) · observed Jul 22, 2026
- GitHub forks (tensorflow/hub) · observed Jul 22, 2026
- Last push (tensorflow/hub) · observed Jan 17, 2025
- License file (Apache-2.0) · observed Jul 22, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (tensorflow/mesh) · observed Aug 7, 2026
- GitHub forks (tensorflow/mesh) · observed Aug 7, 2026
- Last push (tensorflow/mesh) · observed Nov 17, 2023
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: hub 3.5k · mesh 1.6k (synced Jul 22, 2026).
Common questions
- What is the difference between hub and mesh?
- hub: A library for transfer learning by reusing parts of TensorFlow models.. mesh: Mesh TensorFlow: Model Parallelism Made Easier. See the comparison table for live GitHub stats and shared categories.
- When should I choose hub over mesh?
- Choose hub over mesh when Pricing: The core functionalities of hub are free to use with an open-source license; however, additional services or enterprise support might incur costs.; Requirements: Requires a Python environment and TensorFlow installation to operate.; Tags unique to hub: embeddings, image-classification, machine-learning, ml; Also covers Data & Retrieval; When you need to leverage existing TensorFlow models and integrate specific parts of them for tasks like embedding or image-classification without retraining the entire model from scratch.
- When should I choose mesh over hub?
- Choose mesh over hub when Tags unique to mesh: model parallelism; When working on large models that benefit from being split across many devices.
- When should I avoid hub?
- When working strictly with non-TensorFlow frameworks such as PyTorch or MXNet, as hub is built specifically for enhancing and reusing models within TensorFlow. If your project requires a more generalized approach to machine-learning without reliance on pre-existing model components, focusing instead on training models from the ground up.
- When should I avoid mesh?
- If you are looking for a tool that simplifies other aspects of machine learning beyond model-parallel computation. For projects with limited GPU/TPU resources where multi-device parallelism is not required.
- Is hub or mesh more popular on GitHub?
- hub has more GitHub stars (3,522 vs 1,630). Stars measure visibility, not whether either tool fits your constraints.
- Are hub and mesh open source?
- Yes - both are open-source projects on GitHub (hub: Apache-2.0, mesh: Apache-2.0).
- Where can I find alternatives to hub or mesh?
- GraphCanon lists graph-backed alternatives at hub alternatives and mesh alternatives (hub markdown twin, mesh 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, hub or mesh?
- hub: Dormant. mesh: Archived. 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 hub and mesh?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hub trust report; mesh trust report.