Comparison
whisper.cpp vs whisper
Verdict
Pick whisper.cpp if a port of OpenAI's Whisper model to C++, optimized with `ggml`, for lightweight speech-to-text transcription; pick whisper if decisions about Whisper should consider its application in contexts requiring large-scale weak supervision models for speech recognition, especially where robustness is paramount.
Markdown twin · whisper.cpp alternatives · whisper alternatives
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Trust & integrity
| Signal | whisper.cpp | whisper |
|---|---|---|
| Maintenance | Very active (0d since push) As of 5d · github_public_v1 | Steady (87d since push) As of 5d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 5d · github_public_v1 | Not a fork · Organization account As of 5d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 5d · osv@v1 | No published findings from this source as of 2026-07-11 As of 6d · 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
- whisper.cpp
- Port of OpenAI's Whisper model in C/C++ for speech-to-text inference
- whisper
- Robust Speech Recognition via Large-Scale Weak Supervision
Stars
- whisper.cpp
- 52k
- whisper
- 105k
Forks
- whisper.cpp
- 5.9k
- whisper
- 13k
Open issues
- whisper.cpp
- 1.2k
- whisper
- 135
Language
- whisper.cpp
- C++
- whisper
- Python
Adopt for
- whisper.cpp
- A port of OpenAI's Whisper model to C++, optimized with `ggml`, for lightweight speech-to-text transcription.
- whisper
- Decisions about Whisper should consider its application in contexts requiring large-scale weak supervision models for speech recognition, especially where robustness is paramount.
Persona
- whisper.cpp
- -
- whisper
- -
Runtime
- whisper.cpp
- -
- whisper
- -
License
- whisper.cpp
- MIT License - permissive license that allows users to use the software in any way, including closed-source applications.
- whisper
- MIT
Last pushed
- whisper.cpp
- Jul 11, 2026
- whisper
- Apr 15, 2026
Categories
- whisper.cpp
- Inference & Serving, Speech & Audio
- whisper
- Speech & Audio
Trust and health
Maintenance
- whisper.cpp
- Very active (96%)
- whisper
- Steady (60%)
Days since push
- whisper.cpp
- 0d
- whisper
- 87d
Open issues (now)
- whisper.cpp
- 1.2k
- whisper
- 135
OSV dependency advisories
- whisper.cpp
- No lockfile (source not queried)
- whisper
- No published findings from this source as of 2026-07-11
Full report
- whisper.cpp
- Trust report
- whisper
- Trust report
Typed relationship
Choose whisper.cpp if…
- whisper.cpp is primarily C++; whisper is Python.
- Requirements: Requires C++ setup and knowledge; Needs audio files converted into a compatible format supported by `ggml`..
- whisper.cpp is a C/C++ port of the Whisper model, providing an alternative implementation for speech-to-text inference.
- Tags unique to whisper.cpp: inference, speech-to-text, transformer, whisper.
- Also covers Inference & Serving.
- You need a lightweight solution that does not require Python or PyTorch
When NOT to use whisper.cpp
- When you prefer to work with higher-level languages like Python which might offer more ease-of-use and extensive libraries
- If your project requires real-time speech transcription and has limited computational resources as `ggml` optimization might still require significant CPU/GPU power for high-performance
Choose whisper if…
- whisper is primarily Python; whisper.cpp is C++.
- whisper.cpp is a C/C++ port of the Whisper model, providing an alternative implementation for speech-to-text inference.
- Tags unique to whisper: weak supervision.
- When you need a tool that leverages large-scale weak supervision to improve the accuracy and reliability of speech recognition.
When NOT to use whisper
- In scenarios necessitating real-time processing where delays associated with large-scale model inference cannot be tolerated.
- If your project strictly requires open collaboration licensing terms beyond the permissive nature of MIT license, such as those which enforce sharing improvements back into the original repository.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ggml-org/whisper.cpp) · observed Jul 11, 2026
- GitHub forks (ggml-org/whisper.cpp) · observed Jul 11, 2026
- Last push (ggml-org/whisper.cpp) · observed Jul 11, 2026
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (openai/whisper) · observed Jul 12, 2026
- GitHub forks (openai/whisper) · observed Jul 12, 2026
- Last push (openai/whisper) · observed Apr 15, 2026
- License file (MIT) · observed Jul 12, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: whisper.cpp 52k · whisper 105k (synced Jul 11, 2026).
Common questions
- What is the difference between whisper.cpp and whisper?
- whisper.cpp: Port of OpenAI's Whisper model in C/C++ for speech-to-text inference. whisper: Robust Speech Recognition via Large-Scale Weak Supervision. See the comparison table for live GitHub stats and shared categories.
- When should I choose whisper.cpp over whisper?
- Choose whisper.cpp over whisper when whisper.cpp is primarily C++; whisper is Python; Requirements: Requires C++ setup and knowledge; Needs audio files converted into a compatible format supported by
ggml.; whisper.cpp is a C/C++ port of the Whisper model, providing an alternative implementation for speech-to-text inference; Tags unique to whisper.cpp: inference, speech-to-text, transformer, whisper; Also covers Inference & Serving; You need a lightweight solution that does not require Python or PyTorch. - When should I choose whisper over whisper.cpp?
- Choose whisper over whisper.cpp when whisper is primarily Python; whisper.cpp is C++; whisper.cpp is a C/C++ port of the Whisper model, providing an alternative implementation for speech-to-text inference; Tags unique to whisper: weak supervision; When you need a tool that leverages large-scale weak supervision to improve the accuracy and reliability of speech recognition.
- When should I avoid whisper.cpp?
- When you prefer to work with higher-level languages like Python which might offer more ease-of-use and extensive libraries If your project requires real-time speech transcription and has limited computational resources as
ggmloptimization might still require significant CPU/GPU power for high-performance - When should I avoid whisper?
- In scenarios necessitating real-time processing where delays associated with large-scale model inference cannot be tolerated. If your project strictly requires open collaboration licensing terms beyond the permissive nature of MIT license, such as those which enforce sharing improvements back into the original repository.
- Is whisper.cpp or whisper more popular on GitHub?
- whisper has more GitHub stars (104,745 vs 51,715). Stars measure visibility, not whether either tool fits your constraints.
- Are whisper.cpp and whisper open source?
- Yes - both are open-source projects on GitHub (whisper.cpp: MIT, whisper: MIT).
- Where can I find alternatives to whisper.cpp or whisper?
- GraphCanon lists graph-backed alternatives at whisper.cpp alternatives and whisper alternatives (whisper.cpp markdown twin, whisper 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, whisper.cpp or whisper?
- whisper.cpp: Very active. whisper: Steady. 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 whisper.cpp and whisper?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: whisper.cpp trust report; whisper trust report.