---

name: venice-audio-transcription description: Transcribe audio files to text via POST /audio/transcriptions. Covers supported models (Parakeet, Whisper, Wizper, Scribe, xAI STT), accepted containers (wav/flac/m4a/aac/mp4/mp3/ogg/webm), response formats (json/text only), per-model timestamps (word/segment/char), language hints, the 25 MB cap, and per-audio-second pricing. OpenAI-compatible multipart.

Venice Transcription (/audio/transcriptions)

POST /api/v1/audio/transcriptions takes an audio file and returns text. It's OpenAI-compatible with multipart/form-data — the OpenAI SDK's audio.transcriptions.create() works unchanged.

Method	Path	Auth	Notes
POST	/api/v1/audio/transcriptions	Bearer key or x402 (SIWX)	multipart/form-data, file field file, max 25 MB. Billed per second of audio.

Use when

• You need STT (speech-to-text) for voice notes, meetings, podcasts, short audio.
• You need word/segment timestamps for subtitles or chapters.
• You want to pick between Venice-hosted Parakeet, Whisper-family models, ElevenLabs Scribe, or xAI STT.

For video, there is no transcription endpoint any more — POST /video/transcriptions is retired and returns 410. Extract the audio track and send it here, or ask a video-capable chat model via venice-chat.

Minimal request

curl https://api.venice.ai/api/v1/audio/transcriptions \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -F "file=@./meeting.m4a" \
  -F "model=nvidia/parakeet-tdt-0.6b-v3" \
  -F "response_format=json" \
  -F "timestamps=false"

{ "text": "Alright everyone, let's kick off the meeting...", "duration": 184.2 }

With timestamps=true, the JSON also carries a timestamps object (see below).

Request (multipart/form-data)

Only the fields below are read; anything else in the form is ignored.

Field	Type	Default	Notes
file	binary	—	Required. Real file part (no base64). Accepted: wav/wave, flac, m4a, aac, mp4, mp3, ogg/oga, webm. Checked by extension/MIME and then by binary signature. Max 25 MB.
model	string	—	Send it. The OpenAPI schema lists nvidia/parakeet-tdt-0.6b-v3 as default, but that default is never applied: omitting model returns 400 "model is required".
response_format	json / text	json	Only these two. text returns a text/plain body with just the transcript.
timestamps	bool (true/false as form string)	false	Adds timestamps to the JSON response.
language	string	—	ISO 639-1 hint (en, ja, …). Forwarded by Whisper, Wizper, Scribe and xAI STT; ignored by Parakeet (auto-detects).

Response

{
  "text": "…",
  "duration": 184.2,
  "timestamps": {
    "word":    [{ "word": "Alright", "start": 0.12, "end": 0.48 }],
    "segment": [{ "text": "Alright everyone…", "start": 0.12, "end": 4.9 }],
    "char":    [{ "char": "A", "start": 0.12, "end": 0.15 }]
  }
}

duration (seconds) and timestamps are optional. Which timestamp arrays appear depends on the model:

Model	Timestamp granularity
openai/whisper-large-v3	segment + word
fal-ai/wizper	segment
elevenlabs/scribe-v2	word
stt-xai-v1	word
nvidia/parakeet-tdt-0.6b-v3	may include segment, word and/or char

Models

All five are in the live GET /models?type=asr list. Price is model_spec.pricing.per_audio_second.usd.

Model ID	Privacy	Notes
nvidia/parakeet-tdt-0.6b-v3	private	Venice-hosted, fast. Ignores language.
openai/whisper-large-v3	private	Multilingual; language hint; segment + word timestamps.
fal-ai/wizper	private	Whisper v3 variant; language hint; segment timestamps.
elevenlabs/scribe-v2	anonymized	language hint; word timestamps.
stt-xai-v1	anonymized	language hint; word timestamps.

A key with modelPrivacy: PRIVATE_ONLY gets 403 on the anonymized ones (PRIVATE_TEXT keys are not restricted here). Failed transcriptions are not charged.

OpenAI SDK

import OpenAI from 'openai'
import fs from 'node:fs'

const client = new OpenAI({
  apiKey: process.env.VENICE_API_KEY,
  baseURL: 'https://api.venice.ai/api/v1',
})

const out = await client.audio.transcriptions.create({
  file: fs.createReadStream('meeting.m4a'),
  model: 'openai/whisper-large-v3',
  response_format: 'json',
  language: 'en',
  // @ts-expect-error — Venice-specific extra, passes through multipart
  timestamps: true,
})

console.log(out.text)

Long files

There's no server-side chunking, and uploads are capped at 25 MB. Split long recordings client-side (on silence, or fixed segments), transcribe each chunk, then concatenate with offset timestamps.

ffmpeg -i long.mp3 -f segment -segment_time 600 -c copy chunk_%03d.mp3

Errors

Code	Meaning
400	Missing model, bad params (e.g. response_format not json/text), no file part (including a JSON body instead of multipart → "No audio file provided"), unsupported extension/MIME, or unrecognized binary signature.
401	Authentication failed.
402	Insufficient balance. Bearer → {"error":"Insufficient USD or Diem balance…"}, or `"API key USD
403	A PRIVATE_ONLY key calling an anonymized model, or region restriction.
404	Unknown model.
413	File larger than 25 MB ({"code":"PAYLOAD_TOO_LARGE","error":"File exceeds the maximum allowed size of 25 MB."}).
422	Upstream provider couldn't process the audio (zero-length, silent, corrupt, unsupported format or language, provider-side refusal). No suggested_prompt.
429	Rate limited.
500	Inference failure.
502	Temporary upstream ASR failure — {"error":"Audio transcription failed due to a temporary upstream error. Please retry."} (no code field). Retry with backoff.
503	Model temporarily offline — retry with jitter.

See venice-errors for body shapes and retry strategy.

Gotchas

• Always send model — the documented default never applies.
• file must be a real multipart file part. JSON + base64 is not supported.
• There is no verbose_json, srt or vtt. For subtitles, use response_format=json + timestamps=true and render the timings yourself. text drops timestamps entirely.
• Check which granularity your model returns before building on timestamps.word vs timestamps.segment.
• A file with a valid extension but a non-audio binary signature is rejected; re-encode to a standard profile (e.g. MP3 44.1 kHz or 16 kHz).
• On 429, back off; throttle big batches rather than firing everything in parallel.