Comparison
supertonic vs TensorFlowASR
Verdict
Pick supertonic if supertonic provides fast multilingual TTS on-device using ONNX runtime, native to Swift with wide language support; 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 · supertonic alternatives · TensorFlowASR alternatives
GraphCanon updated Sep 20, 2026
17views this month
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Trust & integrity
| Signal | supertonic | TensorFlowASR |
|---|---|---|
| Maintenance | Archived (11d since push) As of Sep 20, 2026 · github_public_v1 | Very active (6d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | Published findings As of Jul 11, 2026 · 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
- supertonic
- Lightning-Fast On-Device Multilingual TTS via ONNX
- TensorFlowASR
- Almost State-of-the-art Automatic Speech Recognition in Tensorflow 2
Stars
- supertonic
- 14k
- TensorFlowASR
- 1.0k
Forks
- supertonic
- 1.5k
- TensorFlowASR
- 237
Open issues
- supertonic
- 131
- TensorFlowASR
- 47
Language
- supertonic
- Swift
- TensorFlowASR
- Python
Adopt for
- supertonic
- Supertonic provides fast multilingual TTS on-device using ONNX runtime, native to Swift with wide language support.
- TensorFlowASR
- TensorFlowASR is an advanced Automatic Speech Recognition library built on TensorFlow 2 that supports modern architectures such as Conformer and RNN-Transducer.
Persona
- supertonic
- -
- TensorFlowASR
- -
Runtime
- supertonic
- -
- TensorFlowASR
- -
License
- supertonic
- MIT
- TensorFlowASR
- Apache-2.0
Last pushed
- supertonic
- Sep 9, 2026
- TensorFlowASR
- Sep 13, 2026
Categories
- supertonic
- Speech & Audio
- TensorFlowASR
- Speech & Audio
Trust and health
Maintenance
- supertonic
- Archived (8%)
- TensorFlowASR
- Very active (96%)
Days since push
- supertonic
- 11d
- TensorFlowASR
- 6d
Archived on GitHub
- supertonic
- Yes
- TensorFlowASR
- No
Open issues (now)
- supertonic
- 131
- TensorFlowASR
- 47
Stars delta
- supertonic
- +242 (30d)
- TensorFlowASR
- 0 (30d)
Open issues delta
- supertonic
- +5 (30d)
- TensorFlowASR
- 0 (30d)
OSV dependency advisories
- supertonic
- No lockfile (source not queried)
- TensorFlowASR
- Published findings
Full report
- supertonic
- Trust report
- TensorFlowASR
- Trust report
Shared compatibility
- Python · supertonic: Python runtime · TensorFlowASR: Python runtime
Choose supertonic if…
- supertonic is primarily Swift; TensorFlowASR is Python.
- License: supertonic is MIT, TensorFlowASR is Apache-2.0.
- Tags unique to supertonic: cpp, csharp, flutter, go.
- When deploying text-to-speech functionality requires swift performance on-device in multiple languages
When NOT to use supertonic
- If the application is multilingual but does not require on-device processing capabilities
- For teams preferring a different primary development language other than Swift or those lacking familiarity with ONNX implementation details
Choose TensorFlowASR if…
- TensorFlowASR is primarily Python; supertonic is Swift.
- License: TensorFlowASR is Apache-2.0, supertonic is MIT.
- 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 (supertone-inc/supertonic) · observed Sep 20, 2026
- GitHub forks (supertone-inc/supertonic) · observed Sep 20, 2026
- Last push (supertone-inc/supertonic) · observed Sep 9, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (TensorSpeech/TensorFlowASR) · observed Sep 20, 2026
- GitHub forks (TensorSpeech/TensorFlowASR) · observed Sep 20, 2026
- Last push (TensorSpeech/TensorFlowASR) · observed Sep 13, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: supertonic 14k · TensorFlowASR 1.0k (synced Sep 20, 2026).
Common questions
- What is the difference between supertonic and TensorFlowASR?
- supertonic: Lightning-Fast On-Device Multilingual TTS via ONNX. 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 supertonic over TensorFlowASR?
- Choose supertonic over TensorFlowASR when supertonic is primarily Swift; TensorFlowASR is Python; License: supertonic is MIT, TensorFlowASR is Apache-2.0; Tags unique to supertonic: cpp, csharp, flutter, go; When deploying text-to-speech functionality requires swift performance on-device in multiple languages.
- When should I choose TensorFlowASR over supertonic?
- Choose TensorFlowASR over supertonic when TensorFlowASR is primarily Python; supertonic is Swift; License: TensorFlowASR is Apache-2.0, supertonic is MIT; 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 supertonic?
- If the application is multilingual but does not require on-device processing capabilities For teams preferring a different primary development language other than Swift or those lacking familiarity with ONNX implementation details
- 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 supertonic or TensorFlowASR more popular on GitHub?
- supertonic has more GitHub stars (13,785 vs 1,010). Stars measure visibility, not whether either tool fits your constraints.
- Are supertonic and TensorFlowASR open source?
- Yes - both are open-source projects on GitHub (supertonic: MIT, TensorFlowASR: Apache-2.0).
- Where can I find alternatives to supertonic or TensorFlowASR?
- GraphCanon lists graph-backed alternatives at supertonic alternatives and TensorFlowASR alternatives (supertonic 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, supertonic or TensorFlowASR?
- supertonic: Archived. 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 supertonic and TensorFlowASR?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: supertonic trust report; TensorFlowASR trust report.