Vertex AI Audio Transcription

Property	Details
Description	Gemini speech-to-text on Vertex AI via the OpenAI /v1/audio/transcriptions endpoint
Provider Route on LiteLLM	vertex_ai/gemini-3.5-transcribe-preview
Supported OpenAI Params	language, response_format (json, text)

Gemini transcribe models on Vertex AI are served from the global location, which LiteLLM uses by default when no vertex_location is set. If you set a regional location (in config, litellm.vertex_location, or the VERTEXAI_LOCATION / VERTEX_LOCATION env vars), that value takes precedence and Vertex returns a 404 for regions where the model is unavailable, so pin vertex_location: global for these models.

Prefer an API key over a GCP service account? The same model is available through Google AI Studio as gemini/gemini-3.5-transcribe.

Quick Start

LiteLLM Python SDK

Gemini Transcribe Quick Start

from litellm import transcription

audio_file = open("speech.wav", "rb")
response = transcription(
    model="vertex_ai/gemini-3.5-transcribe-preview",
    file=audio_file,
    language="en",
    vertex_project="your-project-id",
    vertex_credentials="/path/to/service_account.json",
)
print(response.text)

LiteLLM AI Gateway

1. Setup config.yaml

config.yaml

model_list:
  - model_name: gemini-transcribe
    litellm_params:
      model: vertex_ai/gemini-3.5-transcribe-preview
      vertex_project: "your-project-id"
      vertex_credentials: "/path/to/service_account.json"

2. Start the proxy

Start LiteLLM Proxy

litellm --config /path/to/config.yaml

3. Make requests

curl

Gemini Transcribe Quick Start

curl http://0.0.0.0:4000/v1/audio/transcriptions \
  -H "Authorization: Bearer sk-1234" \
  -F file=@speech.wav \
  -F model=gemini-transcribe \
  -F language=en

OpenAI Python SDK

Gemini Transcribe Quick Start

import openai

client = openai.OpenAI(api_key="sk-1234", base_url="http://0.0.0.0:4000")

audio_file = open("speech.wav", "rb")
response = client.audio.transcriptions.create(
    model="gemini-transcribe",
    file=audio_file,
    language="en",
)
print(response.text)

Supported Params

language accepts two-letter codes or BCP-47 tags and is normalized to BCP-47 before being sent to Gemini. response_format supports json (default) and text; Gemini transcription on Vertex AI returns no word timestamps, so verbose_json, srt, and vtt are rejected with a 400 unless drop_params is set, in which case they are dropped and the plain transcript is returned.

Usage and Cost Tracking

Vertex AI reports token usage split by modality, and LiteLLM tracks audio input tokens and text output tokens separately, so spend logs and the x-litellm-response-cost header reflect Google's published per-token audio transcription pricing.