--- title: "whisper.cpp vs sherpa-onnx" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ggml-org-whisper-cpp-vs-k2-fsa-sherpa-onnx" tools: ["ggml-org-whisper-cpp", "k2-fsa-sherpa-onnx"] --- # whisper.cpp vs sherpa-onnx *GraphCanon updated Jul 12, 2026* ## Verdict Pick whisper.cpp when license: whisper.cpp is MIT, sherpa-onnx is Apache-2.0; pick sherpa-onnx when license: sherpa-onnx is Apache-2.0, whisper.cpp is MIT. [whisper.cpp](https://github.com/ggml-org/whisper.cpp) reports 52k GitHub stars, 5.9k forks, and 1.2k open issues, last pushed Jul 11, 2026. [sherpa-onnx](https://k2-fsa.github.io/sherpa/onnx/index.html) has 13k stars, 1.5k forks, and 600 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [whisper.cpp's repository](https://github.com/ggml-org/whisper.cpp) and [sherpa-onnx's repository](https://github.com/k2-fsa/sherpa-onnx). | | [whisper.cpp](/tools/ggml-org-whisper-cpp.md) | [sherpa-onnx](/tools/k2-fsa-sherpa-onnx.md) | | --- | --- | --- | | Tagline | Port of OpenAI's Whisper model in C/C++ for speech-to-text inference | Speech-to-text, text-to-speech, speaker diarization, speech enhancement, source separation, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android | | Stars | 51,715 | 13,499 | | Forks | 5,898 | 1,545 | | Open issues | 1,216 | 600 | | Language | C++ | C++ | | Adopt for | A port of OpenAI's Whisper model to C++, optimized with `ggml`, for lightweight speech-to-text transcription. | - | | Persona | - | - | | Runtime | - | - | | License | MIT License - permissive license that allows users to use the software in any way, including closed-source applications. | Apache-2.0 | | Categories | Inference & Serving, Speech & Audio | Computer Vision, Inference & Serving, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [whisper.cpp](/tools/ggml-org-whisper-cpp.md) | [sherpa-onnx](/tools/k2-fsa-sherpa-onnx.md) | | --- | --- | --- | | Days since push | 0d | 1d | | Open issues (now) | 1.2k | 600 | | Full report | [trust report](/tools/ggml-org-whisper-cpp/trust.md) | [trust report](/tools/k2-fsa-sherpa-onnx/trust.md) | ## Decision facts: whisper.cpp - **Requirements:** Requires C++ setup and knowledge; Needs audio files converted into a compatible format supported by `ggml`. - **Adopt for:** A port of OpenAI's Whisper model to C++, optimized with `ggml`, for lightweight speech-to-text transcription. - **License detail:** MIT License - permissive license that allows users to use the software in any way, including closed-source applications. ## Choose when ### Choose whisper.cpp if… - License: whisper.cpp is MIT, sherpa-onnx is Apache-2.0. - Requirements: Requires C++ setup and knowledge; Needs audio files converted into a compatible format supported by `ggml`.. - Tags unique to whisper.cpp: inference, openai, speech-recognition, speech-to-text. - You need a lightweight solution that does not require Python or PyTorch ### Choose sherpa-onnx if… - License: sherpa-onnx is Apache-2.0, whisper.cpp is MIT. - Tags unique to sherpa-onnx: aarch64, android, arm32, asr. - Also covers Computer Vision. ## 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 ## When NOT to use sherpa-onnx - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## Common questions ### What is the difference between whisper.cpp and sherpa-onnx? whisper.cpp: Port of OpenAI's Whisper model in C/C++ for speech-to-text inference. sherpa-onnx: Speech-to-text, text-to-speech, speaker diarization, speech enhancement, source separation, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android. See the comparison table for live GitHub stats and shared categories. ### When should I choose whisper.cpp over sherpa-onnx? Choose whisper.cpp over sherpa-onnx when License: whisper.cpp is MIT, sherpa-onnx is Apache-2.0; Requirements: Requires C++ setup and knowledge; Needs audio files converted into a compatible format supported by `ggml`.; Tags unique to whisper.cpp: inference, openai, speech-recognition, speech-to-text; You need a lightweight solution that does not require Python or PyTorch. ### When should I choose sherpa-onnx over whisper.cpp? Choose sherpa-onnx over whisper.cpp when License: sherpa-onnx is Apache-2.0, whisper.cpp is MIT; Tags unique to sherpa-onnx: aarch64, android, arm32, asr; Also covers Computer Vision. ### 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 `ggml` optimization might still require significant CPU/GPU power for high-performance ### When should I avoid sherpa-onnx? Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### Is whisper.cpp or sherpa-onnx more popular on GitHub? whisper.cpp has more GitHub stars (51,715 vs 13,499). Stars measure visibility, not whether either tool fits your constraints. ### Are whisper.cpp and sherpa-onnx open source? Yes - both are open-source projects on GitHub (whisper.cpp: MIT, sherpa-onnx: Apache-2.0). ### Where can I find alternatives to whisper.cpp or sherpa-onnx? GraphCanon lists graph-backed alternatives at [whisper.cpp alternatives](/tools/ggml-org-whisper-cpp/alternatives) and [sherpa-onnx alternatives](/tools/k2-fsa-sherpa-onnx/alternatives) ([whisper.cpp markdown twin](/tools/ggml-org-whisper-cpp/alternatives.md), [sherpa-onnx markdown twin](/tools/k2-fsa-sherpa-onnx/alternatives.md)), 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](/compare/ggml-org-whisper-cpp-vs-k2-fsa-sherpa-onnx.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, whisper.cpp or sherpa-onnx? whisper.cpp: Very active. sherpa-onnx: 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 whisper.cpp and sherpa-onnx? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [whisper.cpp trust report](/tools/ggml-org-whisper-cpp/trust); [sherpa-onnx trust report](/tools/k2-fsa-sherpa-onnx/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ggml-org-whisper-cpp`](/api/graphcanon/graph?tool=ggml-org-whisper-cpp) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_