# Windows and NVIDIA deployment notes

This path is a recommendation for the planned dedicated Windows/NVIDIA host.
It has not yet passed the Local Voice acceptance suite and must be treated as
provisional.

## Recommended host

- Windows 11
- Current NVIDIA Studio or production driver
- Python 3.11 x64
- ffmpeg and Whisper available on `PATH`
- Sufficient SSD space for the 4.7 GB model, jobs, and retained WAV files
- NVIDIA GPU with supported CUDA capability and practical VRAM headroom

## Preferred deployment order

1. Start with native Windows and a CosyVoice3 wheel built for the installed CUDA
   runtime.
2. If native dependency resolution is unreliable, use WSL2 with NVIDIA CUDA
   passthrough and the Linux CUDA build.
3. Use `LOCAL_VOICE_RUNTIME` to point at a dedicated data directory, for example
   `D:\MPM-Local-Voice\runtime`.
4. Copy the same private `voices` archive and model directory used on macOS.
5. Run `doctor --device cuda`.
6. Run the full acceptance suite before scheduling production briefings.

## Important differences

- The verified Metal wheel cannot run on Windows.
- CUDA, driver, and wheel versions must agree.
- Do not assume that a CUDA build exists merely because the NVIDIA driver is
  installed.
- Keep ffmpeg path quoting and Windows long-path behavior in mind.
- Compare transcript coverage, ending confidence, seam derivatives, duration,
  and subjective voice similarity against the macOS acceptance outputs.

## Fallback

CPU generation remains functionally possible but may be slower. It is suitable
for overnight batches if CUDA setup is delayed, provided the acceptance suite
passes on that host.

## Certification checklist

- [ ] `cosyvoice3`, NumPy, and SoundFile import
- [ ] Candle model hashes match the recovery manifest
- [ ] All authorized voice assets resolve
- [ ] CUDA device loads successfully
- [ ] Every acceptance output passes transcript QA
- [ ] Ryan fixed assets and dialogue assembly are seamless
- [ ] Five production briefs can complete inside the overnight window