Overview
Description
WhisperX turns spoken audio into accurate, timestamped text faster than real time. It automatically identifies who said what with speaker labels, making it ideal for transcribing meetings, interviews, and podcasts. No manual editing needed for timing or speaker attribution.
Technical scorecard
License
BSD-2-Clause
Commercial use
Yes
OpenAI-compatible API
No
REST API
No
Fine-tuning support
No
Quantization support
Yes
Docker available
No
GUI / no-code available
No
Telemetry
Unknown
Offline after setup
Yes
Data & Privacy
Does it send data online?
After setup, this listing is marked as usable offline. Confirm network behavior against the upstream project before regulated deployment.
Does it store history?
Not verified in this directory yet. Review the upstream docs for persistence, logs, and workspace storage.
License checks?
Commercial use is marked as allowed or likely allowed by the listed license.
Telemetry?
Unknown
Last verified: Jul 22, 2026. Maintainer verification should be treated as directory guidance, not legal advice.
Deploying WhisperX in production?
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Request Privacy and Telemetry AuditSetup & Installation
A developer can usually get this running with standard docs.
# Start with the official project repository
# https://github.com/m-bain/whisperXHardware Requirements
Works Well With