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audio.cpp Windows prebuilt binaries v0.6

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@0xShug0 0xShug0 released this 13 Aug 18:01
· 3 commits to main since this release
release-0.6
bb15edd
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These Windows prebuilt packages are for audio.cpp 0.6, built from commit bb15edd on main.

What's New in Release 0.6

  • Native WebUI is now embedded in audiocpp_server.exe.

    • No Python, Node.js, or Gradio required for inference UI.
    • Includes model loading/unloading, package install/update status, and native controls.

  • Irodori-TTS v4 Small added.

    • GGUF Q8/F16 support.
    • Supports Japanese no-reference TTS, voice cloning, and voice design in one checkpoint.

  • IndexTTS2.5 added as a new index_tts2 variant.

    • Adds multilingual zero-shot TTS for Chinese, English, Japanese, Spanish, and Arabic.
    • Includes GGUF conversion tooling and native Safetensors staging support.

  • SenseVoice-Small added.

    • Offline and streaming ASR.
    • Supports multilingual transcription with language, emotion, event tags, and ITN.

  • MiniMax-H3 added as an experimental community model.

    • Prompt-driven audio/dialogue/video generation.
    • GGUF Q4/INT8 package support.

  • New TTS/audio families added: DotTTS, NeuTTS, and MuScriptor.

  • GGUF package coverage expanded across the new release models and exposed through the native WebUI/model manager.

Packages

CPU packages are self-contained:

  • audiocpp-windows-cpu-fast.zip
  • audiocpp-windows-cpu-balance.zip
  • audiocpp-windows-cpu-portable.zip

CUDA packages are split into one shared runtime package plus one profile package:

  • audiocpp-windows-cuda-runtime.zip
  • audiocpp-windows-cuda-fast.zip
  • audiocpp-windows-cuda-balance.zip
  • audiocpp-windows-cuda-portable.zip

The CUDA runtime package contains the large CUDA DLLs shared by all CUDA profiles. Download it once, then pair it with whichever CUDA profile package you want to use. You don't need to download it if you already have it from previous releases.

Which Package Should I Download?

Use a CUDA package if you have a supported NVIDIA GPU. CUDA profile packages include both CUDA and CPU backend support, so they can run with either --backend cuda or --backend cpu once the CUDA runtime DLLs are available.

Use a CPU package if you do not have a supported NVIDIA GPU or only want CPU inference.

For most users:

  • NVIDIA GPU: download audiocpp-windows-cuda-runtime.zip and audiocpp-windows-cuda-balance.zip
  • CPU only: download audiocpp-windows-cpu-balance.zip

CPU Architecture Profiles

The package names use three CPU compatibility profiles:

Profile CPU build setting Best for Tradeoff
fast Native CPU optimization Newer high-end x86-64 CPUs that support the same instruction families used by the package Fastest CPU path, but least portable. If your CPU is older or missing newer SIMD instructions, use balance or portable.
balance AVX2 CPU kernels, native CPU optimization off Most modern x86-64 Windows PCs with AVX2 support Recommended default. More portable than fast, faster than portable, and avoids AVX512/AVX-VNNI requirements.
portable Baseline CPU kernels, native CPU optimization off, llamafile SGEMM off Older or unknown x86-64 Windows CPUs Broadest compatibility, but slowest. Avoids AVX, AVX2, AVX512, AVX-VNNI, and llamafile SGEMM.

The CUDA packages still include a CPU backend, so the same CPU profile applies when a CUDA package is run with --backend cpu.

CUDA Package Requirements

  • 64-bit Windows
  • NVIDIA GPU with compute capability 7.5 or newer
  • NVIDIA driver 580 or newer
  • Model files downloaded separately

The CUDA Toolkit and Visual Studio Build Tools are not required to run the CUDA packages. The required CUDA runtime DLLs are provided in audiocpp-windows-cuda-runtime.zip.

The CUDA packages are intended for RTX 20/30/40/50 series GPUs and similar NVIDIA datacenter GPUs. Older GPUs such as GTX 10-series Pascal cards or V100-class Volta cards are not covered by the CUDA 13 package; use a CPU package or build a separate package with an older CUDA Toolkit if those GPUs must be supported.

Quick Start

CPU users: unzip one CPU package, then run:

.\audiocpp_cli.exe --help

CUDA users: unzip audiocpp-windows-cuda-runtime.zip and one CUDA profile package into the same directory, then run:

.\audiocpp_cli.exe --help

CUDA example:

.\audiocpp_cli.exe --backend cuda --task tts --family <family> --model C:\path\to\model [options]

CPU example:

.\audiocpp_cli.exe --backend cpu --task tts --family <family> --model C:\path\to\model [options]

Server:

.\audiocpp_server.exe --config C:\path\to\server.json

Notes

  • Models are not bundled.
  • For CPU packages, keep the bundled DLL files next to the .exe files.
  • For CUDA packages, keep the CUDA runtime DLLs from audiocpp-windows-cuda-runtime.zip next to the .exe files, or put that runtime directory on PATH.
  • If CUDA startup fails, update the NVIDIA driver first.
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