GraphCanon updated 3w · GitHub synced 3w
Decision brief
Whishper is an open-source audio transcription and subtitling suite with a web UI that supports both GPU and CPU for local transcription.
Good fit when
- When you need to transcribe media files locally without sending data to external servers, ensuring privacy.
- For projects or environments where offline functionality is required and internet connectivity can't be assumed.
Avoid when
- When real-time transcription accuracy outweighs local processing needs, because while faster on CPU, it may not offer the same level of immediate precision as cloud-based solutions.
- If your project is resource-constrained, especially in terms of development time and effort required for setup since Whishper involves a few manual steps to start using.
- Pricing:
- freemium - Free, open-source solution that does not charge for usage or require payment plans.
- Requirements:
- Min 4 GB RAM; Requires Docker; Supports both GPU and CPU for processing.; NVIDIA GPU is optional.
Observed Jul 17, 2026 · Source: enrich:decision_facts
Verify the decision
Adoption
Package downloads where a registry match exists. GitHub stars (3,048) are secondary evidence.
- Docker Hub pulls (30d)
- 179,533·Docker Hub API·3w
Maintenance and security
Full trust report- Maintenance
- Slowing (348d since push)
- As of 3w
- Provenance
- Not a fork · Personal account
- As of 3w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/pluja/whishperSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Whishper is an all-in-one solution for transcribing media to text 100% locally using Whisper models. Features include speech recognition, translation services, powerful subtitle editing capabilities, and support for both GPU and CPU.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Jul 30, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Jul 30, 2026
- Languages
- svelte
Source: github.language · Jul 30, 2026
Categories
Tags
README
🚧 I am working on a complete rewrite of the project. Progress on this can be seen at v4 branch. Consequently, this branch will not receive any new releases or updates.
Whishper is an open-source, 100% local audio transcription and subtitling suite with a full-featured web UI.
Features
- 🗣️ Transcribe any media to text: audio, video, etc.
- Transcribe from URLs (any source supported by yt-dlp).
- Upload a file to transcribe.
- 📥 Download transcriptions in many formats: TXT, JSON, VTT, SRT or copy the raw text to your clipboard.
- 🌐 Translate your transcriptions to any language supported by Libretranslate.
- ✍️ Powerful subtitle editor so you don't need to leave the UI!
- Transcription highlighting based on media position.
- CPS (Characters per second) warnings.
- Segment splitting.
- Segment insertion.
- Subtitle language selection.
- 🏠 100% Local: transcription, translation and subtitle edition happen 100% on your machine (can even work offline!).
- 🚀 Fast: uses FasterWhisper as the Whisper backend: get much faster transcription times on CPU!
- 👍 Quick and easy setup: use the quick start script, or run through a few steps!
- 🔥 GPU support: use your NVIDIA GPU to get even faster transcription times!
- 🐎 CPU support: no GPU? No problem! Whishper can run on CPU too.
Roadmap
- Local folder as media input (#15).
- Full-text search all transcriptions.
- User authentication.
- Audio recording from the browser.
- Add insanely-fast-whisper as an optional backend (#53).
-
Support for GPU acceleration.- Non NVIDIA GPU support. Is it possible with faster-whisper?
- Can we do something with seamless_communication?
Project structure
Whishper is a collection of pieces that work together. The three main pieces are:
- Transcription-API: This is the API that enables running Faster-Whisper. You can find it in the
transcription-apifolder. - Whishper-Backend: This is the backend that coordinates frontend calls, database, and tasks. You can find it in
backendfolder. - Whishper-Frontend: This is the frontend (web UI) of the application. You can find it in
frontendfolder. - Translation (3rd party): This is the libretranslate container that is used for translating subtitles.
- MongoDB (3rd party): This is the database that stores all the information about your transcriptions.
- Nginx (3rd party): This is the proxy that allows running everything from a single domain.
Contributing
Contributions are welcome! Feel free to open a PR with your changes, or take a look at the issues to see if there is something you can help with.
Development setup
Check out the development documentation here.
Screenshots
These screenshots are available on the official website, click any of the following links to see:
Support
- Monero:
82x6cn628oTUXV63DxBd6MJB8d997FhaSaGFvoWMgwihVmgiXYQPAwm2BCH31AovA9Qnnv1qQRrJk83TaJ8DaSZU2zkbWfM - Bitcoin:
bc1qfph44jl4cy03stwfkk7g0qlwx2grldr9xpk086 - Lightning Network (kycnotme)
Star History
For agents
This page has a .md twin and JSON over the API.