Pricing
$0.017 per minute (same as OpenAI's official rate, no markup), charged by the audio duration transcribed in real time. Usage is settled to the second, rounded up to the next whole second.
Input Modalities
- Text
- Audio
Output Modalities
- Text
Try this model
# pip install websockets
import asyncio
import base64
import json
import os
import websockets
# Realtime transcription is a WebSocket session: model must be in the handshake URL.
URL = "wss://aihubmix.com/v1/realtime?intent=transcription&model=gpt-live-transcribe"
async def main():
# websockets >= 13 uses additional_headers; older versions use extra_headers
async with websockets.connect(
URL, additional_headers={"Authorization": "Bearer " + os.environ["AIHUBMIX_API_KEY"]}
) as ws:
# 1) Configure the transcription session (first frame; server VAD auto-segments speech as you stream)
await ws.send(json.dumps({
"type": "session.update",
"session": {
"type": "transcription",
"audio": {
"input": {
"format": {
"type": "audio/pcm",
"rate": 24000
},
"transcription": {
"model": "gpt-live-transcribe"
},
"turn_detection": {
"type": "server_vad"
}
}
}
}
}))
flushed = asyncio.Event() # set once the whole stream is sent + flushed
# 2) Stream raw PCM16 / 24kHz / mono audio in ~100ms chunks
async def send_audio():
with open("audio_pcm16_24k.raw", "rb") as f:
pcm = f.read()
chunk = 24000 * 2 * 100 // 1000 # 100ms of 16-bit mono samples
for i in range(0, len(pcm), chunk):
await ws.send(json.dumps({
"type": "input_audio_buffer.append",
"audio": base64.b64encode(pcm[i:i + chunk]).decode(),
}))
await asyncio.sleep(0.1) # simulate realtime pacing
# Server VAD segments on pauses; flush any trailing audio at end of stream
await ws.send(json.dumps({"type": "input_audio_buffer.commit"}))
flushed.set()
asyncio.create_task(send_audio())
# 3) Receive events: deltas stream live; each pause finalizes a segment (server VAD)
async for msg in ws:
evt = json.loads(msg)
etype = evt.get("type", "")
if etype.endswith("transcription.delta"):
print(evt.get("delta", ""), end="", flush=True)
elif etype.endswith("transcription.completed"):
print("\n[segment]", evt.get("transcript", ""))
if flushed.is_set(): # last segment after the final flush → done
break
elif etype == "error":
print("\n[error]", evt.get("error"))
break
asyncio.run(main())Frequently asked questions
What is GPT Live Transcribe?
How much does GPT Live Transcribe cost?
What modalities does GPT Live Transcribe support?
How do I call GPT Live Transcribe via API?
Who created GPT Live Transcribe?
When was GPT Live Transcribe released?
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