GLM-4-Voice
End-to-end Chinese and English spoken dialogue model from Zhipu AI with streaming speech output.
About
An early fully open end-to-end speech chat model, GLM-4-Voice from Zhipu AI holds a conversation in Chinese and English without a separate ASR or TTS pipeline. Three released components divide the work: a speech tokenizer that adds vector quantization to a Whisper encoder and compresses audio to 12.5 discrete tokens per second, the GLM-4-Voice-9B language model, extended from GLM-4-9B with pretraining on millions of hours of audio and interleaved speech-text data, and a flow-matching decoder derived from CosyVoice that can start synthesizing after as few as 10 tokens for low-latency streaming replies. Users can steer emotion, intonation, speaking rate, and dialect through natural language instructions. The repository provides a web demo with bfloat16 and Int4 launch options, and inference requires a CUDA GPU with substantial memory for the 9B model. Code is Apache-2.0 while the model weights carry their own usage agreement on Hugging Face. Released in December 2024 with an accompanying arXiv paper, it became a common baseline for the wave of open speech-to-speech models that followed.
Should you use GLM-4-Voice?
Pick it when
Pick GLM-4-Voice when you need an open end-to-end voice chat baseline for Chinese and English, with natural language control over emotion, rate, and dialect, and a CUDA GPU with enough memory for a 9B model or its Int4 build.
Look elsewhere when
Skip it if you need languages beyond Chinese and English, vision input, or simple commercial terms, since the weights carry their own usage agreement. Kimi-Audio is MIT and Apache licensed, and Qwen2.5-Omni 7B ships Apache-2.0 weights.
Alternatives to GLM-4-Voice
- Kimi-Audio
Broader task coverage (ASR, audio QA, captioning, emotion recognition) in a 7B model under MIT and Apache terms, versus a separate weight agreement here.
- Qwen2.5-Omni
Adds image and video understanding with Apache-2.0 weights on the 7B model, but BF16 needs 31.1 GB of VRAM for 15 seconds of video, and the 3B variant is research licensed.
- Moshi
Full-duplex dialogue that can listen while speaking instead of taking turns, at around 200 ms latency, but it calls for a GPU with about 24 GB.
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Details
- Category
- Audio & Speech
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Intermediate (3/5)
- License
- Apache-2.0
- Added
- Jul 29, 2026