Running in ~30 s
Pre-cached image, ports mapped, TLS terminated — the stack is working before you finish reading this.
Template · Audio & speech · CUDA 12.6
Run Whisper transcription on a cloud GPU, in 30 seconds
Batch-transcribe audio with faster-whisper behind a UI and a REST endpoint. faster-whisper behind a web UI and a REST endpoint: upload files or point it at a folder, get transcripts, subtitles and word timestamps in dozens of languages. A cheap card transcribes hours of audio per hour of GPU time. From $0.020/hr on an interruptible RTX 3060.
Template is free
You pay the GPU price only: Whisper WebUI & API on a RTX 3060 is $0.041/hr on-demand, $0.020/hr interruptible, billed per second.
Volumes for state
Models, datasets and outputs live on a $0.08/GB/mo volume; the instance stays disposable.
Private by default
Dedicated GPU, encrypted disk, crypto payments, no KYC, no stored IPs — Jupyter and SSH behind your own credentials.
Best GPUs for Whisper WebUI & API
Three price points that run this template well — Good, Better, Best. Every model in the catalogue works; these are the value picks.
| Tier | GPU | VRAM | On-demand | Interruptible | Why this card | Action |
|---|---|---|---|---|---|---|
| Good | RTX 3060 | 12 GB | $0.041 | $0.020 | 12 GB runs large-v3 with room to spare — the cheapest transcription box. | Deploy |
| Better | RTX 4070 | 12 GB | $0.066 | $0.033 | Ada speed for batch jobs at a low rate. | Deploy |
| Best | L4 | 24 GB | $0.225 | $0.112 | 72 W datacenter card for an always-on transcription API. | Deploy |
Need more VRAM? The full catalogue lists all 76 models with live availability; the VRAM guide sizes models to cards.
Deploy Whisper WebUI & API from the console, CLI or API
Pick the template in the console deploy bar, or script it:
- Console — filter by GPU, choose Whisper WebUI & API in the template picker, set disk and env, deploy.
- CLI — pip install powergpu, then the command on the right. CLI reference.
- API — POST /v1/instances with "template": "whisper-webui-api". REST reference.
- Own image — any OCI reference works too; we inject the NVIDIA runtime. Template docs.
$ powergpu launch --gpu rtx-3060 --template whisper-webui-api \
--disk 100 --volume models:/workspace/models
✓ instance i-7a41c0e2 running (27.9s)
# Whisper WebUI & API · RTX 3060 · $0.041/hr · per second
# https://i-7a41c0e2.powergpu.io:8888 (TLS)
$ powergpu stop i-7a41c0e2 # billing ends this secondWhat is inside the Whisper WebUI & API template
| Image | powergpu/whisper |
|---|---|
| CUDA | CUDA 12.6 |
| Access | also builds for ARM hosts · SSH shell · JupyterLab on a mapped port |
| Category | Audio & speech |
| Storage | Instance NVMe disk (sized at deploy) + optional network volumes |
| Billing | GPU price only, per second — no template fee, no setup fee |
Other audio & speech templates
Voicebox TTS on a cloud GPU — Text-to-speech and voice cloning with a web interface and API.
ACE Step 1.5 on a cloud GPU — The ACE-Step music generation model with a UI and API.- All 37 templates
Whisper WebUI & API on a cloud GPU: FAQ
Environment variables, ports and custom images are covered in the template docs.
How much does it cost to run Whisper WebUI & API on a cloud GPU?
Only the GPU price — the template is free. From $0.020/hr on an interruptible RTX 3060, $0.041/hr on-demand on a RTX 3060. Billing is per second, so an hour of tinkering costs an hour, not a day. Storage is $0.08/GB/month.
How long does Whisper WebUI & API take to start?
About 30 seconds from the deploy click: the image is pre-cached on hosts, ports are mapped and TLS is terminated for you. Restarting a stopped instance is faster, and your disk is exactly as you left it.
Can I keep my models and outputs between sessions?
Yes — attach a volume at deploy. Everything on the volume survives instance destruction and mounts on the next instance in the region in seconds, at $0.08/GB/month. The instance disk itself survives stop/start but not destroy.
How fast is transcription?
faster-whisper large-v3 transcribes roughly 20–40× real time on an RTX 4070 with batching — an hour of audio in about two minutes.