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aufklarer/VoxCPM2-MLX-bf16

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face
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Model Card

VoxCPM2 — MLX bf16

Full-precision MLX port for Apple Silicon.

MLX port of openbmb/VoxCPM2 — a 2B-parameter multilingual diffusion-autoregressive TTS model with 48 kHz studio-quality output, voice cloning, and instruction-driven voice design.

Part of soniqo.audio — an on-device speech toolkit for Apple Silicon. Consumed by the open-source `speech-swift` library (module VoxCPM2TTS).

Bundle size: 4.96 GB

Use cases

Variants

VariantSizeNotes
bf16~5.0 GBReference quality, no Linear quantization.
int8~3.0 GB8-bit group quantization. Mean rel-L2 0.53 % vs bf16.

Capabilities

  • 30 languages including English, Chinese, Indonesian, Japanese, Korean
  • 48 kHz output
  • Zero-shot synthesis — generate speech from text alone
  • Voice cloning — clone a target speaker from a single reference clip
  • Voice design — natural-language style control (e.g. "young female voice, warm and gentle")
  • Ultimate cloning — reference audio + transcript for prosody-preserving cloning
  • Streaming generation — patch-level decoding for low-latency synthesis

Precision

No quantization. All Linear weights stored as bfloat16. Use this variant for reference quality or when memory is not a constraint.

Usage with speech-swift

This bundle is consumed by soniqo/speech-swift's VoxCPM2TTS Swift module.

swift
import VoxCPM2TTS

let model = try await VoxCPM2TTSModel.fromPretrained(
    modelId: "aufklarer/VoxCPM2-MLX-bf16"
)
let audio = try await model.generate(text: "Hello from VoxCPM2.", language: "english")

Or via the CLI:

bash
speech speak "Hello from VoxCPM2." --engine voxcpm2 --voxcpm2-variant bf16 -o hi.wav

Source

This bundle is converted from the upstream PyTorch weights at openbmb/VoxCPM2.

License

Apache 2.0 — inherited from the upstream openbmb/VoxCPM2 model.

Responsible use

Voice cloning capability is included. Users are responsible for obtaining consent for any voice that is cloned and for not using the model to impersonate individuals without their permission, generate disinformation, or commit fraud.