zai-org/GLM-TTS

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1055 stars · 136 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

GLM-TTS is a Python-based text-to-speech synthesis system built on large language models, using a two-stage LLM plus Flow model architecture. It supports zero-shot voice cloning from short audio prompts, emotion-expressive speech via multi-reward reinforcement learning, and real-time streaming inference.

Use cases

• clone a voice from a few seconds of audio
• generate emotional expressive speech from text
• stream tts audio in real time for interactive apps
• synthesize chinese and mixed chinese-english speech
• run text-to-speech locally on gpu or npu
• build a voice assistant with custom speaker voice

When to choose

• you need zero-shot voice cloning with only 3-10 seconds of reference audio
• you want controllable emotion and prosody in synthesized speech
• you need streaming tts for real-time or interactive applications
• your primary language is Chinese with some English mixed in
• you want an open-source Apache-2.0 TTS model you can self-host

When to avoid

• you need production-grade multilingual support beyond Chinese and English
• you have no GPU or NPU available for inference
• you need a lightweight CPU-only TTS solution
• you require a mature stable API with long-term support guarantees
• you need non-Python integration without wrapping the model

Facets

library · maturity active

tts speech-recognition llm-inference machine-learning deep-learning speech-processing artificial-intelligence large-language-models python cross-platform zero-shot-voice-cloning text-to-speech reinforcement-learning streaming-inference emotion-control voice-cloning flow-model chinese npu-support natural-language-processing gpu linux

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markdown · JSON · MCP: product_card(name="zai-org/GLM-TTS")