Skip to main content

Documentation Index

Fetch the complete documentation index at: https://runcrate.ai/docs/llms.txt

Use this file to discover all available pages before exploring further.

Convert text to natural-sounding speech with a single API call. Choose from lightweight models for real-time applications or larger models for studio-quality output.

​
Available TTS models

ModelParametersStrengths
hexgrad/Kokoro-82M82MUltra-fast, low-latency, good for real-time apps
canopylabs/orpheus-3b-0.1-ft3BExpressive speech with emotion control
Qwen/Qwen3-TTS—Multilingual, high-quality prosody

​
Generate speech

curl https://api.runcrate.ai/v1/audio/speech \
  -H "Authorization: Bearer rc_live_YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "hexgrad/Kokoro-82M",
    "input": "Welcome to Runcrate. Your GPU instance is ready.",
    "voice": "af_heart"
  }' \
  --output welcome.mp3

​
Expressive speech with Orpheus

Orpheus 3B supports emotion tags for more expressive output: 
from openai import OpenAI
from pathlib import Path

client = OpenAI(
    base_url="https://api.runcrate.ai/v1",
    api_key="rc_live_YOUR_API_KEY",
)

response = client.audio.speech.create(
    model="canopylabs/orpheus-3b-0.1-ft",
    input="I just got the results back, and — honestly — I could not be happier.",
    voice="tara",
)

Path("expressive.mp3").write_bytes(response.content)

​
Multilingual speech with Qwen TTS

Qwen/Qwen3-TTS handles multiple languages automatically — pass text in any supported language and the model detects it: 
from openai import OpenAI
from pathlib import Path

client = OpenAI(
    base_url="https://api.runcrate.ai/v1",
    api_key="rc_live_YOUR_API_KEY",
)

response = client.audio.speech.create(
    model="Qwen/Qwen3-TTS",
    input="Bienvenido a nuestra plataforma. Su cuenta está lista.",
)
Path("spanish.mp3").write_bytes(response.content)

​
Next steps