[audio.cpp] 10 hours of audio generated in 3 minutes on RTX 5090 (demo included)! C++/GGML based Supertonic 3, MOSS-TTS, IndexTTS2, and Irodori-TTS released
Summary
Release of C++/GGML based implementations of Supertonic 3, MOSS-TTS, IndexTTS2, and Irodori-TTS in audio.cpp, capable of generating 10 hours of audio in 3 minutes on an RTX 5090.
Similar Articles
[audio.cpp] Release 0.4: Higgs Audio v3 TTS 4B (10x real time)+ Fish Audio S2 Pro in C++/GGML, full GGUF loading, Q8 speed and VRAM gains
Release 0.4 of audio.cpp adds C++/GGML inference for Higgs Audio v3 TTS 4B (10x real-time) and Fish Audio S2 Pro, with full GGUF loading and Q8 speed/VRAM gains.
[audio.cpp] The Sound of GGML — C++/GGML native ACE-Step, Stable Audio, HeartMuLa, RoFormer, HTDemucs released. 10-Minute Music in 60 Seconds!
audio.cpp releases a major update adding music/SFX generation and source separation with ACE-Step, HeartMuLa, Stable Audio 3, and HTDemucs, achieving up to 10x real-time speed for long music generation in native C++/GGML.
audio.cpp: 12 audio models (Qwen3-TTS, PocketTTS, VeVo2 etc) in 1 C++/ggml runtime — TTS up to 5x faster than Python on CUDA
audio.cpp is a C++/ggml runtime that integrates 12 audio models including Qwen3-TTS, PocketTTS, and VeVo2, achieving TTS up to 5x faster than Python on CUDA.
[audio.cpp] VibeVoice 1.5B released — 90-min podcast in 22.95 min, 4.08x real-time, 2.86x faster than Python without quantization. Native C++/ggml
VibeVoice 1.5B, a long-form multi-speaker TTS model, is now supported in audio.cpp, a native C++/ggml runtime, achieving 4.08x real-time speed on RTX 5090, 2.86x faster than Python baseline without quantization.
[audio.cpp] What Does the Fox Say: 4 ASR models (Nemotron 3.5 ASR, Higgs Audio STT, VibeVoice ASR, and Hviske ASR) in native C++/GGML, init streaming support, and 327s of audio transcribed in 2.17s.
audio.cpp update introduces streaming support and four ASR/STT models (Nemotron 3.5, Higgs Audio STT, VibeVoice ASR, Hviske ASR) in native C++/GGML, achieving up to 2.41x faster than Python with competitive WER and VRAM usage.