Inference APIs

Measured accuracy

ModelWord error rateCharacter error rateClips with no errorsEmpty transcriptsSpeed
Whisper Large v3
openai/whisper-large-v3
33%9.1%0 of 300 of 300.063× real time

Fair. Gets the content across, but needs a human pass before it is published or quoted. The clips are clean, single-speaker read speech, so treat this as a best case for your own recordings. How we measured, and all 83 languages.

What a transcript looks like

The clip with the median error rate from the test, reference text against what the API returned.

SpokenParagvæ hefur tekist að halda í mikið af frumbyggjaeðli sínu og sjálfsmynd frá stofnun Asunción árið 1537.
Whisper Large v3Paraguay hefur tekist að halda ímeku af frumbyggjaðið sínu og sjálfsmynd frá stopnum Assunción árið 1537.

Language detection

All 10 clips we sent without a language field were identified as Icelandic. Auto-detection is safe here; sending language=is still skips the detection step.

Quickstart

The request is the OpenAI transcription request with a different base URL. language is optional.

cURL
curl https://api.inferenceapis.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $INFERENCE_API_KEY" \
  -F "model=openai/whisper-large-v3" \
  -F "language=is" \
  -F "file=@recording.mp3" \
  -F "response_format=verbose_json"
Python · openai SDK
import os
from openai import OpenAI

client = OpenAI(base_url="https://api.inferenceapis.com/v1", api_key=os.environ["INFERENCE_API_KEY"])
with open("recording.mp3", "rb") as f:
    r = client.audio.transcriptions.create(model="openai/whisper-large-v3", file=f, language="is", response_format="verbose_json")
print(r.text)

Subtitles and timestamps

response_format=srt or vtt returns a subtitle file with cues of up to two lines, broken at sentence ends and pauses. verbose_json with timestamp_granularities[]=word returns a start and end time for every word if you want to build your own.

Cost

$0.002 per minute of audio on either model: $0.12 for an hour, $12 for a hundred hours. Duration is measured from the file you upload. There is no daily cap on minutes and no subscription; enough to run your own Icelandic test.

FAQ

How accurate is Whisper for Icelandic?

On 30 clean read-speech clips it made 33% word errors, about one word in 3. Gets the content across, but needs a human pass before it is published or quoted. Real recordings with noise, accents or several speakers will score worse.

Does language auto-detection work for Icelandic?

In our test, yes: all 10 clips sent without a language were identified as Icelandic. Sending language=is still saves the detection step on every request.

Can it translate Icelandic speech to English?

The API returns Icelandic text. For English, transcribe first and translate the text with a chat model on the same key.

Related languages: Faroese · Norwegian (9.7%) · Danish (15%)