mudler/MOSS-TTS-Local-Transformer-v1.5-GGUF

MOSS-TTS-Local-Transformer-v1.5 (GGUF)

Brought to you by the LocalAI team.

GGUF conversion of OpenMOSS-Team/MOSS-TTS-Local-Transformer-v1.5 for moss-tts.cpp: a C++17/ggml inference port of the OpenMOSS MOSS-TTS family that runs entirely on stock ggml with no Python, ONNX or torch at inference time.

Architecture

MossTTSLocal v1.5 is an RQ-Transformer text-to-speech model:

• Global backbone: a 36-layer Qwen3 transformer over time (the text + speech prefix), hidden size 2560.
• Local depth transformer: a 1-layer GPT-J block (LayerNorm, fused QKV, interleaved RoPE, SiLU MLP) over the codebooks within each frame.
• Binary decision head: a direct 2-wide local_text_head on channel 0 that chooses continue (audio slot) vs stop (audio end) per frame.
• 12 RVQ codebooks decoded through MOSS-Audio-Tokenizer-v2 at 48 kHz stereo (interleaved output).

The non-matmul tensors (all lc.* heads and embeddings, every norm and bias) are kept in f32 in every quant; only the Qwen3 global and GPT-J local attention/FFN matmuls are quantized, so the CPU gather/head paths stay exact.

Verification

This port is numerically verified against the reference PyTorch implementation: the language model matches to about 1e-5 with an exact greedy code sequence, and the MOSS-Audio-Tokenizer-v2 decode matches at about 115 dB SNR (bit-exact in f32). On CPU it runs roughly twice as fast per frame as the reference PyTorch at the same f32 precision.

Files

quant	size	notes
f16	9.4 GB	half precision, code-exact vs f32
q8_0	6.0 GB	8-bit, near-lossless, recommended default

The non-matmul path (heads, embeddings, norms, biases) stays f32 in both quants. This repo also ships the codec (moss-audio-tokenizer-v2-f32) and tokenizer (moss-tokenizer-v1_5) GGUFs required to run the model.

Usage

With moss-tts.cpp built:

moss-tts-cli tts-local \
    --model moss-tts-local-v1_5-q8_0.gguf \
    --codec moss-audio-tokenizer-v2-f32.gguf \
    --tokenizer moss-tokenizer-v1_5.gguf \
    --text "Hello from the LocalAI team." \
    --out out.wav

The output is a 48 kHz stereo WAV. Swap --model for any of the quants above.

Links

• Inference engine: https://github.com/mudler/moss-tts.cpp
• Base model: https://huggingface.co/OpenMOSS-Team/MOSS-TTS-Local-Transformer-v1.5
• Codec: https://huggingface.co/OpenMOSS-Team/MOSS-Audio-Tokenizer-v2

License

Released under the Apache-2.0 license, following the upstream base model.