Text-to-speech / MODEL API
Qwen3-TTS
Output $2 / 1M tokens
OVERVIEW
Model overview
Qwen3-TTS covers 10 major languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian) as well as multiple dialectal voice profiles to meet global application needs. In addition, the models feature strong contextual understanding, enabling adaptive control of tone, speaking rate, and emotional expression based on instructions and text semantics, and they show markedly improved robustness to noisy input text.
Specifications
- Category
- Text-to-speech
- Input modalities
- text
- Output modalities
- audio
MODEL PRICING
Model API pricing
Text-to-speech
USD per 1M tokens| Model | Input | Output |
|---|---|---|
| Qwen3-TTS | — | $2 |
Public platform rates refresh every five minutes. A dash means a rate is not provided; it does not mean free. Check the console for final charges.
BUILT FOR YOUR STACK
API quickstart
Expand connection setup and run the preparation commands first. Then save and run the Python or cURL example.
Connection setup & preparationActual API address, model ID, and environment variables
- API address
https://api.ecohash.com/v1- API model ID
qwen3-tts
Replace YOUR_API_KEY with the full inference API key issued in the console. Run setup in macOS/Linux or a compatible shell. JSON cURL examples use the Python standard library to build the request body.
python -m pip install openai
export GIGACOMMA_API_BASE_URL='https://api.ecohash.com/v1'
export GIGACOMMA_MODEL_ID='qwen3-tts'
export GIGACOMMA_API_KEY="YOUR_API_KEY"GIGACOMMA_API_KEY is the environment variable name. Its value is an inference API key from the console, not an OpenAI API key. Get an API key
import osfrom openai import OpenAIMODEL_ID = os.environ["GIGACOMMA_MODEL_ID"]client = OpenAI( base_url=os.environ["GIGACOMMA_API_BASE_URL"], api_key=os.environ["GIGACOMMA_API_KEY"],)with client.audio.speech.with_streaming_response.create( model=MODEL_ID, input="Hello, welcome to GIGACOMMA!", voice="Cherry", response_format="wav",) as response: response.stream_to_file("speech.wav")