---
format: "aidr-story-markdown/v1"
id: "9f15985d4d9e965409cdc27f65b5b1b8b58c5b5b1a697ef0b94efb154acb0007"
canonical_url: "https://aidr.today/9f15985d?lang=en"
title: "Deploying real-time personalized speech with Qwen3-TTS on Amazon SageMaker AI"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
translation_fallback: null
fallback_fields: []
published_at: "2026-09-25T16:09:46.000Z"
category: "Models"
topics: ["amazon","inference"]
source_urls: ["https://aws.amazon.com/blogs/machine-learning/deploying-real-time-personalized-speech-with-qwen3-tts-on-amazon-sagemaker-ai/"]
summary: "Deploy the publicly available Qwen3-TTS-12Hz-1.7B-Base text-to-speech model from Amazon SageMaker JumpStart to a fully managed, real-time endpoint, and clone a voice from a short reference clip. Cross-lingual cloning preserves the speaker's identity across languages."
---

# Deploying real\-time personalized speech with Qwen3\-TTS on Amazon SageMaker AI

> [Open the canonical story](<https://aidr.today/9f15985d?lang=en>)

**Published:** 2026-09-25T16:09:46.000Z
**Category:** Models
**Topics:** amazon, inference

## Summary

Deploy the publicly available Qwen3\-TTS\-12Hz\-1\.7B\-Base text\-to\-speech model from Amazon SageMaker JumpStart to a fully managed, real\-time endpoint, and clone a voice from a short reference clip\. Cross\-lingual cloning preserves the speaker's identity across languages\.

## Sources

- [Story source](<https://aws.amazon.com/blogs/machine-learning/deploying-real-time-personalized-speech-with-qwen3-tts-on-amazon-sagemaker-ai/>)