whisper-ctranslate2
Whisper command line client compatible with original OpenAI client based on CTranslate2
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
whisper-ctranslate2 is a speech-to-text tool that offers a command-line interface for Whisper models using CTranslate2, ensuring compatibility with the original OpenAI client.
Good fit when
- Use whisper-ctranslate2 when you need a command-line interface for Whisper models that is compatible with the original OpenAI client and leverages CTranslate2 for performance.
- Opt for whisper-ctranslate2 if you are working in an environment where Docker is preferred for deployment, as it provides a prebuilt Docker image that includes the small, medium, and large-v2 models.
Avoid when
- Avoid whisper-ctranslate2 if you do not have access to a GPU and require a tool that performs well without GPU acceleration.
- Do not use whisper-ctranslate2 if you need a tool that supports models not included in the prebuilt Docker image and you cannot or do not want to create a derived Docker image or use Docker volumes.
Observed Sep 18, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (215d since push)
- As of Sep 18, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 18, 2026
- Security (OSV)
- No criticals
- As of Sep 18, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install whisper-ctranslate2How it fits your stack(1)
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Overview
A speech-to-text tool that provides a command-line interface for Whisper models using CTranslate2, compatible with the original OpenAI client.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Sep 18, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Sep 18, 2026
- Languages
- python
Source: github.language · Sep 18, 2026
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README
Using prebuild Docker image You can use build docker image. First pull the image: docker pull ghcr.io/softcatala/whisper ctranslate2:latest The Docker image includes the small, medium and large v2 models. To run it: docker run gpus "device=0" \ v "$(pwd)":/srv/files/ \ it ghcr.io...
For agents
This page has a .md twin and JSON over the API.