Fast-Whisper

Fast-Whisper is a high-performance local STT using CTranslate2. Provides 2-4x faster inference than standard Whisper with support for CPU and GPU acceleration.

Vision Agents uses Stream Video for real-time WebRTC transport by default. External WebRTC transports are supported as well. Most AI providers offer free tiers to get started.

Installation

uv add "vision-agents[fast-whisper]"

Quick Start

from vision_agents.core import Agent, User
from vision_agents.plugins import fast_whisper, gemini, elevenlabs, getstream

agent = Agent(
    edge=getstream.Edge(),
    agent_user=User(name="Assistant", id="agent"),
    instructions="You are a helpful assistant.",
    llm=gemini.LLM("gemini-3-flash-preview"),
    stt=fast_whisper.STT(model_size="base"),
    tts=elevenlabs.TTS(),
)

Fast-Whisper runs locally. No API key required. Models download automatically on first use.

Parameters

Name	Type	Default	Description
model_size	str	"base"	Model size ("tiny", "base", "small", "medium", "large-v3")
language	str	None	Language code or None for auto-detect
device	str	"cpu"	Device ("cpu", "cuda", "auto")
compute_type	str	"int8"	Precision ("int8", "float16", "float32")

Model Sizes

Model	Speed	Use Case
tiny	Fastest	Real-time, resource-constrained
base	Very Fast	General purpose
small	Fast	Balanced
medium	Moderate	Higher accuracy
large-v3	Slower	Maximum accuracy

Optimization

# CPU (default) - use int8 for best performance
stt = fast_whisper.STT(device="cpu", compute_type="int8")

# GPU - use float16 for speed and accuracy
stt = fast_whisper.STT(device="cuda", compute_type="float16")

Next Steps

Build a Voice Agent

Get started with voice

Build a Video Agent

Add video processing