---
license: apache-2.0
language: [zh, en]
tags: [tts, gguf, moss, jetson, ggml, edge]
base_model: OpenMOSS-Team/MOSS-TTS-Nano-100M
---
# MOSS-TTS-Nano-100M — GGUF (Q8_0) for RapidSpeech.cpp / ggml-CUDA

Q8_0 GGUF conversion of [OpenMOSS-Team/MOSS-TTS-Nano-100M](https://huggingface.co/OpenMOSS-Team/MOSS-TTS-Nano-100M)
for on-device inference on Jetson Nano gen1 (Maxwell sm_53) via ggml-CUDA.

- `moss_nano_full.gguf` — **merged AR model + codec decoder**, Q8_0 (~138 MB from 440 MB fp32).
  - AR: GPT-2 12-layer global + 1-layer local decoder + 16 audio codebook heads (interleaved RoPE, gelu_new).
  - Codec: MOSS-Audio-Tokenizer-Nano decoder + 16-way RVQ (weight_norm reconstructed) → 48 kHz.
- `moss_nano.gguf` — AR model only. `moss_codec.gguf` — codec only.

**Verified** (torch-free, vs the deployed ONNX): global transformer prefill+decode MSE 1.4e-6,
local decoder 14/16 argmax (Q8), codec round-trip corr 0.95–0.998.
**Performance** (Jetson Nano GPU, ggml-CUDA): Q8 RTF 0.86 (full 12L) / 0.50 (4L student);
~0.35 with the custom sm_53 matvec kernel. RTF floor ~0.12.

Runtime: [vieenrose/RapidSpeech.cpp](https://github.com/vieenrose/RapidSpeech.cpp) (branch jetson-nano-gen1),
arch `moss_tts_nano`. Converters in `scripts/convert_moss_*_to_gguf.py`.