Text-to-speech Sourced statement

Pocket TTS on Mac (Apple Silicon M1–M4)

Benchmark pending. We haven't measured this pair yet. Below is what the sources say about this hardware, quoted with links.

Unified memory shared by CPU and GPU. Runtime support varies a lot (Metal via whisper.cpp/MLX; PyTorch MPS is often partial).

EvidenceSourced statement
Commercial useYes
Licensecc-by-4.0
Stated memoryNot stated
Device memory16 GB unified memory

Results

Benchmark pending. No measured numbers from us yet for Pocket TTS on Apple Silicon. Get notified or send us your numbers (with the method).

What the sources say about Apple Silicon

  • Model authors ~6x real time on the CPU of a MacBook Air M4 (vendor). source

Method

We haven't run this pair. Everything on this page is quoted from the linked sources, with the source type labelled (model authors vs third parties). Vendor numbers are often measured under favourable conditions.

Ways to run Pocket TTS

RuntimePrecisionDocumented devices
pocket-tts (PyTorchfp32, int8 dynamic quant (CPU only)CPU (GPU optional)source
sherpa-onnx (third-party)ONNXWindows/macOS/Linux, Raspberry Pi, Jetson, RK3588source
MLX port (communityMLXApple Siliconsource

Run it

pip install pocket-tts      # Linux: add --extra-index-url https://download.pytorch.org/whl/cpu to skip CUDA wheels
pocket-tts generate

Copied from the linked README. We haven't run it on this device.

New open speech models: will they run on your hardware?

One email a week: new open TTS/STT models, license gotchas, and what we measured on CPUs, Macs, Pis and consumer GPUs.