MDisBetter vs OpenAI Whisper — Hosted vs Open-Source ASR
OpenAI Whisper is the open-source automatic speech recognition model that effectively reset the field in 2022 — runs locally with Python and a GPU (or slowly on CPU), free if you have hardware, plain text output. MDisBetter is a hosted service built on top of similar primitives, with structured Markdown output and zero setup. The choice is rarely about output quality (both are good) and almost always about whether you want to operate the inference yourself.
| Feature | MDisBetter | OpenAI Whisper |
|---|---|---|
| Audio → text transcription | ✓ | ✓ |
| Output format | Structured Markdown (speakers + H2 + timestamps) | Plain text / JSON / SRT / VTT |
| Speaker diarization | ✓ | No (need WhisperX or pyannote on top) |
| Setup | None — upload a file | Python + GPU + model weights download |
| Cost — single-file use | Free tier | Free if you have hardware |
| Cost — at scale (1000h/mo) | Pro tier | GPU server + ops time |
| Languages supported | ~50 languages | ~99 languages |
| Runs locally / private data | No (Enterprise tier on roadmap) | Yes — your hardware, your data |
| Hosted API | ✕ | Yes via OpenAI API (paid, separate) |
Frequently asked questions
When should I pick Whisper over MDisBetter?
Three cases: (1) audio so sensitive it cannot leave your network (medical recordings, privileged interviews, internal HR), (2) volume so large that GPU economics beat per-minute pricing (think hundreds of hours per month), (3) you need a language we don't cover well — Whisper handles ~99 languages versus our ~50. For everything else, the operational overhead of running Whisper yourself outweighs the cost of a hosted service.
Is Whisper as accurate as MDisBetter?
On clean English audio, comparable — both are based on modern ASR pipelines and produce ~95–98% word-level accuracy on standard recordings. Whisper has a slight edge on low-resource languages thanks to broader training; MDisBetter's edge shows up downstream in the structured Markdown output that saves you the formatting step.
Does Whisper handle speaker diarization?
Not by itself — vanilla Whisper outputs continuous text with no speaker labels. To add diarization you stack WhisperX or pyannote on top, which is a few hours of additional setup plus model downloads. MDisBetter ships diarization by default in the Markdown output.
Can I use Whisper via OpenAI's API instead of self-hosting?
Yes — OpenAI's Whisper API (~$0.006/minute as of recent pricing) gives you the model without the GPU. That's a different product from open-source Whisper — convenient but not free, and still plain text output without diarization or Markdown structure. MDisBetter's Pro covers the full suite at $10/month flat.
Can I use both?
Yes, and many teams do. Whisper self-hosted for the small subset of audio that must stay on-prem; MDisBetter for everything else where hosted convenience and structured Markdown output matter. Outputs are interoperable since both produce text.