MODEL PROFILE

Yue2-3B-GGUF

audio-cpp · Yue2-3B-GGUF

This repository contains audio.cpp-native GGUF weights for Yue2-3B. The model has been merged into the main branch. The demos below were generated with `yue2-3b-bf16.gguf` and `yue2-vae-f32.gguf`. The `_q8.wav` comparison files were generated with `yue2-3b-q8_0.gguf` and `yue2-vae-f16.gguf` using the same prompts and seeds. The `_q4_0.wav` comparison files were generated with `yue2-3b-q4_0.gguf` and `yue2-vae-f16.gguf`. Replace ` ` with your audio.cpp checkout and ` ` with this downloaded GGUF repo directory. To generate the Q4_0 versions, use the same commands and replace `--session-option yue2.model_gguf=yue2-3b-bf16.gguf` with `--session-option yue2.model_gguf=yue2-3b-q4_0.gguf`, and use `--session-option yue2.vae_gguf=yue2-vae-f16.gguf`. Measured with audio.cpp server mode on an RTX 5090, using the official `tonight-awake` longform example. Each run restarted the server and used one short warmup request before the measured longform request. Peak VRAM was sampled continuously during the measured request.

Speech synthesislicense:cc-by-nc-4.0
Context windowNot disclosed
Input → OutputText → Audio
Model weightsNot verified
Profile updated2026/10/29 10:26:34
OVERVIEW

Model overview

This repository contains audio.cpp-native GGUF weights for Yue2-3B. The model has been merged into the main branch. The demos below were generated with `yue2-3b-bf16.gguf` and `yue2-vae-f32.gguf`. The `_q8.wav` comparison files were generated with `yue2-3b-q8_0.gguf` and `yue2-vae-f16.gguf` using the same prompts and seeds. The `_q4_0.wav` comparison files were generated with `yue2-3b-q4_0.gguf` and `yue2-vae-f16.gguf`. Replace ` ` with your audio.cpp checkout and ` ` with this downloaded GGUF repo directory. To generate the Q4_0 versions, use the same commands and replace `--session-option yue2.model_gguf=yue2-3b-bf16.gguf` with `--session-option yue2.model_gguf=yue2-3b-q4_0.gguf`, and use `--session-option yue2.vae_gguf=yue2-vae-f16.gguf`. Measured with audio.cpp server mode on an RTX 5090, using the official `tonight-awake` longform example. Each run restarted the server and used one short warmup request before the measured longform request. Peak VRAM was sampled continuously during the measured request.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

Source prices & cost analysis

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

Do open weights permit free commercial use?

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Sources & traceability

许可证:cc-by-nc-4.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。