Whisper hosting

Private speech-to-text behind your own transcription API.

Speech, image & videoMITfrom $12.99/mo
In short

Whisper hosting at AIHostBox means a dedicated, single-tenant Whisper instance on our infrastructure: we install it, pin it to a reviewed release, put it behind TLS on your domain, back it up nightly and keep it patched. Plans start at $12.99 per month and the admin account, the data and any API keys are yours.

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Whisper transcribes audio across dozens of languages, and the optimised CPU builds we deploy (faster-whisper) make that practical without a GPU. You get an API endpoint that accepts an audio file and returns text, timestamps and optional translation — the same shape as the commercial transcription APIs, at a flat monthly price.

This ladder buys cores rather than memory, because transcription is CPU-bound. On the Starter plan the base and small models run comfortably faster than real time; the Pro plan handles medium and large-v3-turbo for higher accuracy work.

Whisper hosting plans

Starterbase / small models
4 GB RAM · 4 vCPU · NVMe
$12.99/mo
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Promedium / large-v3-turbo
8 GB RAM · 6 vCPU · NVMe
$21.99/mo
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Every plan is a dedicated single-tenant instance with NVMe storage, nightly off-box backups, TLS and managed patching. Quarterly, semi-annual and annual terms are discounted at checkout. Model tokens are not included — you bring your own key.

How we run Whisper

The whisper-asr-webservice container (CPU build) on port 9000 running the faster-whisper engine with int8 quantization, with model files cached on a persistent volume.

What we configure for you

  • ASR_ENGINE=faster_whisper and ASR_DEVICE=cpu, which defaults ASR_QUANTIZATION to int8
  • ASR_MODEL chosen for your plan (base or small on Starter, medium or large-v3-turbo on Pro)
  • ASR_MODEL_PATH on a persistent volume so models are not downloaded on every restart
  • MODEL_IDLE_TIMEOUT if you would rather free memory between infrequent jobs
  • TLS on your subdomain, with the API not left open to the public because the service has no login of its own

Which plan fits

Starter (4 GB, 4 vCPU) runs base and small comfortably, which suits meeting notes, voice memos and clear podcast audio. Pro (8 GB, 6 vCPU) is for medium and large-v3-turbo, where accents, crosstalk or technical vocabulary need the extra accuracy and six cores keep turnaround reasonable.

The honest limits

Everything runs on CPU, so large models approach real-time speed rather than beating it, and one long file will hold the queue. The upstream API is its own REST shape (/asr), not a drop-in copy of OpenAI’s /v1/audio/transcriptions route.

What people run Whisper for

Meeting transcription

Recordings in, searchable text out, nothing sent to a vendor.

Podcast and video subtitles

Timestamped output ready for caption files.

Call analysis

Feed transcripts into a model for summaries and tagging.

Licence and version policy

ItemPosition
Upstream licenceMIT
Sold as managed hostingYes
TenancySingle tenant — one customer per instance
PatchingCritical advisories within 24 hours, high severity within 72

Our full position on licences, including the applications we decline to sell, is on the licensing page.

Reading on Whisper

Works well with Whisper

More Speech, image & video we host

Questions

Whisper hosting: your questions

How fast is it without a GPU?
With faster-whisper on dedicated cores, small models transcribe several times faster than real time; large models are closer to real time. Tell us your volume and we will point you at the right tier.
Is my audio stored?
Only if you configure it that way. The default is transcribe and discard; the instance is yours either way.
Which Whisper models can I run?
The service takes ASR_MODEL values from tiny, base and small through medium, large-v3 and large-v3-turbo, plus the English-only .en variants. On Starter we recommend base or small; on Pro, medium or large-v3-turbo, which gives near-large accuracy at a fraction of large-v3’s cost. Changing model is a restart, not a rebuild.
What output formats and options does the API support?
The /asr endpoint accepts an audio or video file and returns text, JSON, VTT, SRT or TSV. You can set the language or leave it to detect, choose task=transcribe or task=translate for English output, and with the faster-whisper engine request word_timestamps and a vad_filter that skips silence. A separate /detect-language endpoint checks the first 30 seconds.
Can it tell speakers apart?
Speaker diarization is available in the underlying service only with the WhisperX engine, which also needs a Hugging Face token for the pyannote model. It is heavier than faster-whisper and slow on CPU, so we enable it only on request on the Pro plan and after testing it against your recordings.
Can I send it video files or phone recordings directly?
Yes. Uploads are converted with FFmpeg before transcription, so common formats such as MP3, M4A, WAV, OGG and MP4 work without preprocessing. Very long files are best sent one at a time; the service processes requests in turn rather than in parallel on CPU.

Run Whisper without running a server

A dedicated Whisper instance, deployed and maintained by us. Month to month, cancel whenever.