Whisper Base API

deepgram/whisper-base
Whisper: Multilingual speech recognition model, robust, versatile, open-source.
Output
$0.000058333 / sec
Released
Dec 30, 2025

Overview

What is Whisper Base API?

Whisper: Multilingual speech recognition model, robust, versatile, open-source.

Technical Specifications
- Supported inputs: Audio
- Output: Text

Performance Benchmarks
[embed]

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.

Use cases

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.

How to use Whisper Base API

Install any OpenAI-compatible SDK, point it at api.aimlapi.com/v1, and set the model to deepgram/whisper-base.
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.

Whisper Base API Pricing

TypePrice
Output
$0.000058333 / sec

Whisper Base Benchmarks

BenchmarkScoreWhat it measuresSourceRetrieved
FLEURS WER
12.4
WER on multilingual speech (102 languages)SourceSeptember 21, 2026
LibriSpeech WER
196.8
Word Error Rate on read English speech (lower better)SourceSeptember 21, 2026

Whisper Base vs other models

ModelInputOutputContextBest for
Whisper Base
This page
$0.000058333 / sec
Transcription
$100 / 1M characters
$130 / 1M
Speech synthesis
$100 / 1M characters
$0.13 / 1M tokens
Speech synthesis
$60 / 1M characters
$0.078 / 1M tokens
Speech synthesis
$10 / 1M characters
$0.013 / 1M tokens
Speech synthesis

Frequently asked questions

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.

Start building with Whisper Base

Get API Key
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