What is Whisper Base API?
Whisper: Multilingual speech recognition model, robust, versatile, open-source.
Technical Specifications
- Supported inputs: Audio
- Output: Text
Performance Benchmarks
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Whisper Base API Pricing
- Pricing on request
Where to Use Whisper Base
Transcription
Convert calls, meetings, and media into accurate, searchable text.
Captioning and indexing
Generate subtitles and make audio archives searchable.
Whisper Base is a speech-to-text model available through Deepgram Whisper Cloud, with the model identifier whisper-base. It is suitable for transcribing recorded speech into text, such as meetings, interviews, lectures, and voice notes.
It can also be used for captioning spoken audio in media workflows, where audio content needs text output for display alongside video or live playback. Another direct use case is call or voicemail transcription, since Deepgram documents base-model variants for phonecall and voicemail transcription within its speech-to-text lineup.
import requests, time headers = {"Authorization": "Bearer " + AIMLAPI_KEY} job = requests.post( "https://api.aimlapi.com/v1/stt/create", headers=headers, json={ "model": "deepgram/whisper-base", "url": "https://example.com/audio.mp3" }, ).json() gid = job["generation_id"] while True: res = requests.get(f"https://api.aimlapi.com/v1/stt/{gid}", headers=headers).json() if res.get("status") in ("completed", "error", "failed"): break time.sleep(3) print(res)
const headers = { Authorization: `Bearer ${process.env.AIMLAPI_KEY}`, "Content-Type": "application/json", }; const job = await (await fetch("https://api.aimlapi.com/v1/stt/create", { method: "POST", headers, body: JSON.stringify({ "model": "deepgram/whisper-base", "url": "https://example.com/audio.mp3" }), })).json(); let res; do { await new Promise((r) => setTimeout(r, 3000)); res = await (await fetch(`https://api.aimlapi.com/v1/stt/${job.generation_id}`, { headers })).json(); } while (!["completed", "error", "failed"].includes(res.status)); console.log(res);
# submit the job — the response contains "generation_id" curl -X POST https://api.aimlapi.com/v1/stt/create \ -H "Authorization: Bearer $AIMLAPI_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"deepgram/whisper-base","url":"https://example.com/audio.mp3"}' # then poll for the result until it is ready curl "https://api.aimlapi.com/v1/stt/{generation_id}" -H "Authorization: Bearer $AIMLAPI_KEY"
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Output | |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
Whisper Base This page | Transcription | |||
| Speech synthesis | ||||
| Speech synthesis | ||||
| Speech synthesis | ||||
| Speech synthesis |
Whisper Base takes audio as input and returns text.
Whisper Base became available on December 30, 2025.
Whisper Base is priced at output $0.00007583 / sec.
Whisper Base was built by Deepgram.
Use deepgram/whisper-base as the model id on AI/ML API.
Yes. Whisper Base is served through AI/ML API, so the same key and endpoint format used for other models applies.
Yes, Whisper Base is described as a multilingual speech recognition model.
Yes, Deepgram describes Whisper Base as an open-source speech recognition model.