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VoiceStudio — MOSS-TTS-v1.5 Engine

MOSS-TTS-v1.5 (OpenMOSS) is an 8B flagship zero-shot TTS — a Qwen3-8B language backbone plus a 1.6B audio codec. It covers 31 languages, does zero-shot voice cloning, token-level duration control and inline [pause Ns] markers. Released under Apache-2.0 (code + weights).

It runs in its own subprocess and its own Python venv with transformers==5.0.0, isolated from the VoiceStudio parent process which pins transformers>=5.3. This is the same isolation primitive used by IndexTTS-2: the two transformers pins cannot share one interpreter, so MOSS runs behind backend/services/subprocess_backend.py::SubprocessBackend.

Opt-in, and never a default. MOSS-TTS-v1.5 is selected explicitly in Model Catalogue (or OMNIVOICE_TTS_BACKEND=moss-tts-v15). It is not part of the default install and does not change VoiceStudio's out-of-the-box behaviour on any platform.

Hardware

  • VRAM/RAM: an 8B model. The upstream llama.cpp pipeline fits the 8B on 8 GB GPUs when quantized; the bf16 Transformers path used here is ~16 GB of weights, so a 16 GB+ GPU is the realistic CUDA target. It also runs on CPU (fp32) — correct but slow.
  • Device: the sidecar uses a runtime-available PyTorch CUDA/ROCm, XPU, or registered NPU backend, otherwise CPU. The isolated engine venv needs the matching torch/vendor integration. A failed accelerator probe falls back to CPU, including in older venvs without the unified accelerator API. MPS still uses CPU. XPU/NPU routing is covered by mocked loader tests; physical-device synthesis has not been validated by this change.

One-click install

On a machine with an NVIDIA GPU, Model Catalogue → MOSS-TTS-v1.5 → Install does every step below for you. It installs into its own folder under VoiceStudio's data directory, with its own Python environment. Nothing it installs touches VoiceStudio itself or any other engine, so you can switch to it and back without breaking what already worked. Uninstall in the same row removes only that folder. The ~16 GB of weights still download on first synthesis. On a CPU-only host the button is not offered; use the manual install.

The first synthesis downloads the weights, which takes a while on a slow connection. The generation stays alive while the download makes progress; if a stalled download runs out of time, raise the compute-time budget in Settings → Performance & Device and try again.

Install

MOSS-TTS-v1.5 is not bundled (the model is large and the package pins a conflicting transformers). VoiceStudio ships a sidecar runner that loads it into an isolated venv on demand.

  1. Clone the MOSS-TTS repo on disk:

    git clone https://github.com/OpenMOSS/MOSS-TTS.git

  2. Install the editable package into a fresh venv. Use uv pip install -e ".[torch-runtime]" — never uv sync --all-extras, which would overwrite VoiceStudio's lock file with transformers==5.0 and break the parent process. The torch-runtime extra is CUDA (+cu128):

    cd MOSS-TTS
uv venv .venv
uv pip install -e ".[torch-runtime]"      --extra-index-url https://download.pytorch.org/whl/cu128      --index-strategy unsafe-best-match

    The extra pins torch==2.9.1+cu128, which is published only on PyTorch's own index, so the --extra-index-url is required — without it uv reports the requirements as unsatisfiable on every host.

    On a non-CUDA / CPU host (e.g. Apple Silicon), install plain torch/torchaudio/transformers==5.0.0 into the venv instead of the +cu128 extra (the auto-bootstrap below only targets CUDA hosts).

  3. The ~16 GB weights download from HuggingFace on first synthesize. The parent forwards HF_HOME / HF_HUB_CACHE to the sidecar so the cache is shared with the rest of VoiceStudio's downloads.

  4. Set OMNIVOICE_MOSS_TTS_V15_DIR to the repo root (the directory that contains pyproject.toml):

    # macOS / Linux
echo 'export OMNIVOICE_MOSS_TTS_V15_DIR=$HOME/code/MOSS-TTS' >> ~/.zshrc
source ~/.zshrc
    # Windows PowerShell
[Environment]::SetEnvironmentVariable("OMNIVOICE_MOSS_TTS_V15_DIR","$env:USERPROFILE\code\MOSS-TTS","User")

  5. Restart VoiceStudio. MOSS-TTS-v1.5 appears in Model Catalogue with available: true and isolation_mode: subprocess.

Venv resolution order

VoiceStudio probes for a usable MOSS Python interpreter in this priority order (see backend/engines/moss_tts_v15/bootstrap.py):

  1. ${OMNIVOICE_MOSS_TTS_V15_DIR}/.venv/ — your existing clone's venv. Highest priority, so a power user who already set MOSS up gets zero re-install.
  2. backend/engines/moss_tts_v15/.venv/ — VoiceStudio's own venv, created on demand by step 3.
  3. Lazy bootstrap — if neither venv exists, VoiceStudio runs uv venv then uv pip install --python <python> -e "${DIR}[torch-runtime]". Requires OMNIVOICE_MOSS_TTS_V15_DIR; raises a clear error otherwise. On a non-CUDA host the +cu128 extra cannot resolve — set the venv up manually per step 2.

Voice cloning

Pass a reference clip as ref_audio. MOSS's zero-shot clone mode needs only the audio (no transcript). Without a reference, MOSS synthesizes in its own default voice. duration (seconds) maps to MOSS's tokens argument at ~12.5 tokens/second.

Optional env knobs

Variable Default Purpose
OMNIVOICE_MOSS_TTS_V15_DIR — Path to the MOSS-TTS clone (required).
OMNIVOICE_MOSS_TTS_V15_MODEL OpenMOSS-Team/MOSS-TTS-v1.5 Advanced HF repo override. Custom repositories execute their modelling code and are rejected unless both safeguards below are set. Configure HF_ENDPOINT for a mirror instead.
OMNIVOICE_MOSS_TTS_V15_REVISION — Immutable 40-character commit SHA required with a custom model repository.
OMNIVOICE_MOSS_TTS_V15_TRUST_REMOTE_CODE — Set to 1 only after auditing a custom repository's Python code. The reviewed built-in repository needs no opt-in.
OMNIVOICE_MOSS_TTS_V15_ATTN sdpa Attention impl; set flash_attention_2 on Ampere+ CUDA with flash-attn installed.

Common errors

MOSS-TTS-v1.5 venv not found. Set OMNIVOICE_MOSS_TTS_V15_DIR ...

You haven't pointed VoiceStudio at a MOSS-TTS clone yet. Follow Install.

uv pip install -e failed ... '[torch-runtime]' extra (cu128) cannot resolve

You're on a non-CUDA host. The upstream torch-runtime extra is CUDA-only; set up the venv manually with plain torch/transformers==5.0.0 (step 2).

License

Apache-2.0 (code and weights) — no acceptance gate. See the upstream README.

MOSS-TTS-v1.5 runs in a dedicated sidecar venv (it pins transformers==5.0, which conflicts with the parent's transformers>=5.3). For why that adds disk and how uv keeps the cost down, see Engine venvs & disk usage.