Comparison
silero-models vs TensorFlowASR
Verdict
Pick silero-models if provides simple access to pre-trained text-to-speech models for various languages via PyTorch Hub, pip installation, and manual caching; pick TensorFlowASR if tensorFlowASR is an advanced Automatic Speech Recognition library built on TensorFlow 2 that supports modern architectures such as Conformer and RNN-Transducer.
Markdown twin · silero-models alternatives · TensorFlowASR alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | silero-models | TensorFlowASR |
|---|---|---|
| Maintenance | Steady (55d since push) As of 3w · github_public_v1 | Very active (0d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 3w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No published findings from this source as of 2026-07-11 As of 1mo · osv@v1 | Published findings 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
- silero-models
- Silero Models provide simple access to pre-trained text-to-speech models
- TensorFlowASR
- Almost State-of-the-art Automatic Speech Recognition in Tensorflow 2
Stars
- silero-models
- 6.0k
- TensorFlowASR
- 1.0k
Forks
- silero-models
- 369
- TensorFlowASR
- 239
Open issues
- silero-models
- 12
- TensorFlowASR
- 47
Language
- silero-models
- Jupyter Notebook
- TensorFlowASR
- Python
Adopt for
- silero-models
- Provides simple access to pre-trained text-to-speech models for various languages via PyTorch Hub, pip installation, and manual caching.
- TensorFlowASR
- TensorFlowASR is an advanced Automatic Speech Recognition library built on TensorFlow 2 that supports modern architectures such as Conformer and RNN-Transducer.
Persona
- silero-models
- -
- TensorFlowASR
- -
Runtime
- silero-models
- -
- TensorFlowASR
- -
License
- silero-models
- Other
- TensorFlowASR
- Apache-2.0
Last pushed
- silero-models
- Jun 4, 2026
- TensorFlowASR
- Jul 30, 2026
Categories
- silero-models
- Speech & Audio
- TensorFlowASR
- Speech & Audio
Trust and health
Maintenance
- silero-models
- Steady (60%)
- TensorFlowASR
- Very active (96%)
Days since push
- silero-models
- 55d
- TensorFlowASR
- 0d
Open issues (now)
- silero-models
- 12
- TensorFlowASR
- 47
Owner type
- silero-models
- User
- TensorFlowASR
- Organization
OSV dependency advisories
- silero-models
- No published findings from this source as of 2026-07-11
- TensorFlowASR
- Published findings
Full report
- silero-models
- Trust report
- TensorFlowASR
- Trust report
Shared compatibility
- Python · silero-models: Python runtime · TensorFlowASR: Python runtime
Choose silero-models if…
- silero-models is primarily Jupyter Notebook; TensorFlowASR is Python.
- License: silero-models is Other, TensorFlowASR is Apache-2.0.
- Tags unique to silero-models: armenian, azerbaijani, belarus, colab.
- Need easy integration of text-to-speech functionalities in Jupyter Notebooks
When NOT to use silero-models
- Require advanced customization of the speech synthesis process beyond provided options
- Looking for a full end-to-end speech recognition (speech-to-text) solution, as this mainly focuses on text-to-speech
Choose TensorFlowASR if…
- TensorFlowASR is primarily Python; silero-models is Jupyter Notebook.
- License: TensorFlowASR is Apache-2.0, silero-models is Other.
- Tags unique to TensorFlowASR: automatic-speech-recognition, conformer, contextnet, ctc.
- TensorFlowASR ships Docker support for self-hosted deployment.
- When focusing on state-of-the-art performance with models like Conformer or ContextNet, which are among its supported architectures and not necessarily included in all ASR libraries.
When NOT to use TensorFlowASR
- When Python version constraints are an issue, as TensorFlowASR strictly requires python >= 3.12 on Apple Silicon devices, limiting compatibility.
- If your project cannot accommodate the extra installation steps involving `ctc_decoders` and `rnnt_loss`, which implies additional complexity in setting up the environment.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (snakers4/silero-models) · observed Jul 29, 2026
- GitHub forks (snakers4/silero-models) · observed Jul 29, 2026
- Last push (snakers4/silero-models) · observed Jun 4, 2026
- License file (Other) · observed Jul 29, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (TensorSpeech/TensorFlowASR) · observed Jul 31, 2026
- GitHub forks (TensorSpeech/TensorFlowASR) · observed Jul 31, 2026
- Last push (TensorSpeech/TensorFlowASR) · observed Jul 30, 2026
- License file (Apache-2.0) · observed Jul 31, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: silero-models 6.0k · TensorFlowASR 1.0k (synced Jul 29, 2026).
Common questions
- What is the difference between silero-models and TensorFlowASR?
- silero-models: Silero Models provide simple access to pre-trained text-to-speech models. TensorFlowASR: Almost State-of-the-art Automatic Speech Recognition in Tensorflow 2. See the comparison table for live GitHub stats and shared categories.
- When should I choose silero-models over TensorFlowASR?
- Choose silero-models over TensorFlowASR when silero-models is primarily Jupyter Notebook; TensorFlowASR is Python; License: silero-models is Other, TensorFlowASR is Apache-2.0; Tags unique to silero-models: armenian, azerbaijani, belarus, colab; Need easy integration of text-to-speech functionalities in Jupyter Notebooks.
- When should I choose TensorFlowASR over silero-models?
- Choose TensorFlowASR over silero-models when TensorFlowASR is primarily Python; silero-models is Jupyter Notebook; License: TensorFlowASR is Apache-2.0, silero-models is Other; Tags unique to TensorFlowASR: automatic-speech-recognition, conformer, contextnet, ctc; TensorFlowASR ships Docker support for self-hosted deployment; When focusing on state-of-the-art performance with models like Conformer or ContextNet, which are among its supported architectures and not necessarily included in all ASR libraries.
- When should I avoid silero-models?
- Require advanced customization of the speech synthesis process beyond provided options Looking for a full end-to-end speech recognition (speech-to-text) solution, as this mainly focuses on text-to-speech
- When should I avoid TensorFlowASR?
- When Python version constraints are an issue, as TensorFlowASR strictly requires python >= 3.12 on Apple Silicon devices, limiting compatibility. If your project cannot accommodate the extra installation steps involving
ctc_decodersandrnnt_loss, which implies additional complexity in setting up the environment. - Is silero-models or TensorFlowASR more popular on GitHub?
- silero-models has more GitHub stars (6,030 vs 1,010). Stars measure visibility, not whether either tool fits your constraints.
- Are silero-models and TensorFlowASR open source?
- Yes - both are open-source projects on GitHub (silero-models: Other, TensorFlowASR: Apache-2.0).
- Where can I find alternatives to silero-models or TensorFlowASR?
- GraphCanon lists graph-backed alternatives at silero-models alternatives and TensorFlowASR alternatives (silero-models markdown twin, TensorFlowASR 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, silero-models or TensorFlowASR?
- silero-models: Steady. TensorFlowASR: 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 silero-models and TensorFlowASR?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: silero-models trust report; TensorFlowASR trust report.