Desktop GUI built for Faster-Whisper-XXL

Transcribe audio faster.
Keep workflows simple.

Download YouTube audio or video, batch transcribe local files, and switch between custom Hugging Face models with a clean, GPU-aware interface.

Local + YouTube Ingest
Custom Hugging Face Models
Multi-format Export
Faster Whisper XXL
Faster Whisper XXL GUI screenshot

Full pipeline control.

Every step of the transcription workflow is streamlined and heavily optimized within a unified interface.

Smart Ingestion

Drag and drop local files, paste YouTube links directly, or batch process entire directories effortlessly.

Multiple Outputs

Export simultaneously to JSON, VTT, SRT, LRC, TXT, and TSV formats.

.JSON.VTT.SRT.LRC.TXT.TSV

Hardware Aware

Hardware optimization can recommend GPU/CPU, model, and compute settings for your system.

On-the-fly Conversion

If a repo has Transformers-only weights, the app prompts (or auto-converts) to CT2 so it can run in Faster-Whisper-XXL.

Model Control

Enable, verify, and switch built-in or custom models directly in Manage Models.

Fast setup, fast results.

From launch to output in three simple steps.

01

Launch & Auto-Download

On first run, the app can download Faster-Whisper-XXL and FFmpeg dependencies if they are missing.

02

Configure & Queue

Select your desired model, transcription/translation task, and check the output formats you need. Drop in your files.

03

Transcribe & Export

Monitor real-time progress. Save outputs to your chosen output folder or next to the source media.

Custom models, no manual conversion scripts.

Bring in any Hugging Face model and keep your pipeline consistent. CT2 repos download directly, while Transformers-only repos prompt conversion (or auto-convert if enabled). EXE builds can use a converter bundle; source builds use your configured Python environment.

Read the Documentation
# Enter Hugging Face repo ID or URL
Fetch "Systran/faster-whisper-large-v3"
>> Download model files from repo metadata
>> If model.bin exists: use as-is (CTranslate2 ready)
>> If only Transformers weights: prompt/auto-convert to CT2
>> Done when model.bin is created (ready to transcribe)

Ready to optimize your workflow?

Grab the standalone executable or build it directly from source.