> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fluidinference.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Getting Started

> möbius — convert AI models for edge deployment on Apple Silicon, NPUs, and other accelerators.

[möbius](https://github.com/FluidInference/mobius) is a model conversion framework for running AI on edge devices. It converts models from PyTorch/ONNX to CoreML, ONNX Runtime, and OpenVINO — targeting Apple Neural Engine, NPUs, and embedded accelerators.

Every model that ships in FluidAudio was converted through möbius.

## Why möbius

Running AI on NVIDIA GPUs is straightforward. The edge is a different story — fragmented devices, different accelerators, format incompatibilities. möbius handles the conversion, validation, and quantization so you get production-ready models with a few commands.

Each conversion includes:

* **Parity validation** — numerical comparison between PyTorch and converted outputs
* **Latency benchmarks** — Torch CPU vs CoreML (ANE/GPU) on real inputs
* **Quantization sweeps** — size, speed, and quality trade-offs for int8, palettization, etc.

## Repository Structure

Models are organized by class, name, and target runtime. Each target directory is self-contained with its own `pyproject.toml` and dependencies managed by [uv](https://github.com/astral-sh/uv).

```
models/
├── emb/
│   └── cam++/coreml                  # Speaker embedding
├── segment-text/
│   └── coreml                        # Text segmentation
├── speaker-diarization/
│   ├── pyannote-community-1/coreml   # Pyannote diarization
│   └── sortformer-streaming/         # Sortformer diarization
├── stt/
│   ├── canary-1b-v2/coreml           # Canary ASR
│   ├── nemotron-speech-streaming-0.6b/coreml
│   ├── parakeet-realtime-eou-120m/coreml
│   ├── parakeet-tdt-ctc-110m/coreml
│   ├── parakeet-tdt-v2-0.6b/coreml
│   ├── parakeet-tdt-v3-0.6b/coreml   # Current FluidAudio default
│   └── qwen3-asr-0.6b/coreml
├── tts/
│   ├── kokoro/coreml                 # Kokoro TTS
│   └── pocket_tts/coreml             # PocketTTS
└── vad/
    └── silero-vad/coreml             # Silero VAD
```

## Converted Models

These models have been converted and published to [Hugging Face](https://huggingface.co/FluidInference):

| Class           | Model                | Source                                                                      | CoreML                                                                              |
| --------------- | -------------------- | --------------------------------------------------------------------------- | ----------------------------------------------------------------------------------- |
| **STT**         | Parakeet TDT v3 0.6B | [NVIDIA](https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3)                | [FluidInference](https://huggingface.co/FluidInference/parakeet-tdt-0.6b-v3-coreml) |
| **STT**         | Parakeet TDT v2 0.6B | [NVIDIA](https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2)                | [FluidInference](https://huggingface.co/FluidInference/parakeet-tdt-0.6b-v2-coreml) |
| **STT**         | Parakeet EOU 120M    | [NVIDIA](https://huggingface.co/nvidia/parakeet-tdt_ctc-110m)               | [FluidInference](https://huggingface.co/FluidInference/parakeet-eou-120m-coreml)    |
| **VAD**         | Silero VAD v6        | [Silero](https://github.com/snakers4/silero-vad)                            | [FluidInference](https://huggingface.co/FluidInference/silero-vad-coreml)           |
| **Diarization** | Pyannote Community 1 | [Pyannote](https://huggingface.co/pyannote/speaker-diarization-community-1) | [FluidInference](https://huggingface.co/FluidInference/speaker-diarization-coreml)  |
| **TTS**         | Kokoro 82M           | [Hexgrad](https://huggingface.co/hexgrad/Kokoro-82M)                        | [FluidInference](https://huggingface.co/FluidInference/kokoro-82m-coreml)           |
| **TTS**         | PocketTTS 155M       | [Kyutai](https://huggingface.co/kyutai/pocket-tts)                          | [FluidInference](https://huggingface.co/FluidInference/pocket-tts-coreml)           |
| **Embedding**   | CAM++                | [3D-Speaker](https://github.com/alibaba-damo-academy/3D-Speaker)            | [FluidInference](https://huggingface.co/FluidInference/cam-plusplus-coreml)         |

## Quick Start

```bash theme={null}
# Clone
git clone https://github.com/FluidInference/mobius.git
cd mobius

# Pick a model
cd models/stt/parakeet-tdt-v3-0.6b/coreml

# Set up environment
uv sync

# Convert
uv run python convert-parakeet.py convert \
  --nemo-path /path/to/parakeet-tdt-0.6b-v3.nemo \
  --output-dir parakeet_coreml

# Validate parity
uv run python compare-components.py compare \
  --output-dir parakeet_coreml \
  --runs 10 --warmup 3
```

Each model directory has its own README with specific conversion steps.

## Conversion Guidelines

* **Trace with `.CpuOnly`** — ensures deterministic tracing without ANE/GPU side effects
* **Target iOS 17+ / macOS 14+** — minimum deployment target for all CoreML exports
* **Use `uv`** — each model has isolated dependencies via its own `pyproject.toml`
* **Validate numerically** — always compare converted outputs against PyTorch reference

## License

Apache 2.0. See individual model directories for upstream model licenses.