VoxCPM2 — LiteRT (INT8)
2 B-parameter multilingual TTS with voice cloning and voice design. 48 kHz output.
Part of the soniqo.audio speech toolkit — an open, runtime-portable stack for speech AI. This bundle is the LiteRT export, designed to plug into the abstract interfaces in
speech-core(C++ voice-agent orchestration library). Browse all LiteRT bundles in the soniqo LiteRT collection.
Use cases on soniqo.audio
LiteRT export of openbmb/VoxCPM2
— a 2 B-parameter diffusion-autoregressive TTS with 48 kHz
studio-quality output, reference-audio voice cloning, and
natural-language voice design. Designed for server-side
synthesis workers and on-device TTS through the
speech-core
TTSInterface.
Why split graphs
VoxCPM2 is not a single feed-forward model. The runtime loop is
text + optional instruction ──► text-prefill
│
▼
repeated token-step
│
▼
audio-decoder ──► 48 kHz PCM
The host owns the loop and the KV cache; LiteRT owns the static tensor programs. Same split used for Parakeet and Nemotron in this collection — LiteRT for the math, host for the control flow.
Files
| File | Size | Description |
|---|---|---|
voxcpm2-text-prefill.tflite | 7.7 GB | FP32 text + instruction prefill (MiniCPM-4 KV-cache producer) |
voxcpm2-token-step.tflite | 2.0 GB | INT8 weight-only autoregressive step (MiniCPM-4 + residual LM) |
voxcpm2-audio-encoder.tflite | 184 MB | FP32 reference-audio encoder (16 kHz → conditioning) |
voxcpm2-audio-decoder.tflite | 175 MB | FP32 AudioVAE decoder (acoustic tokens → 48 kHz PCM) |
tokenizer.json / tokenizer_config.json / special_tokens_map.json | — | HF tokenizer bundle |
generation_config.json / tokenization_voxcpm2.py | — | Generation defaults + tokenizer module |
config.json | — | Tensor shapes, sample rates, files manifest |
Quantization
- token-step: INT8 weight-only (the only graph that runs in the inner generation loop — quantizing here is the biggest win).
- text-prefill / audio-encoder / audio-decoder: stay FP32. Quantizing prefill caused semantic drift in roundtrip; the AudioVAE decoder is audible-risky under INT8.
Smoke result
30-step English roundtrip ("hello world from soniqo dot audio",
instruction "clear neutral delivery"):
- Stop token fired naturally at step 18 (decoder halted before the 30-step ceiling)
- 138 240 samples × 48 kHz mono = 2.88 s
- RMS 0.033, peak 0.44 — no clipping, real signal level
- Output written to
voxcpm2-litert-hello-world.wav
Modes
Mirrors the speech-swift VoxCPM2TTS
mode matrix:
| Mode | Inputs |
|---|---|
| Zero-shot | text |
| Voice design | text + style instruction |
| Controllable cloning | text + reference audio |
| Ultimate cloning | text + reference audio + prompt audio + prompt text |
For Apple Silicon, prefer the MLX bundles
(bf16 /
int8 /
int4)
consumed by speech-swift.
Source
Exported from openbmb/VoxCPM2 via a graph-split LiteRT conversion, run in a pinned Docker environment because LiteRT / Torch / TorchAO versions are tightly coupled.
Responsible use
Voice cloning is included. Users are responsible for obtaining consent for any voice that is cloned and for not using the model to impersonate individuals without permission, generate disinformation, or commit fraud.
Ecosystem
- soniqo.audio — use-case explorer (transcription, voice cloning, live ASR, voice agents).
- speech-core — C++ orchestration library for voice agents. Abstract
STTInterface/TTSInterface/VADInterface/EnhancerInterface; LiteRT implementations plug straight into the interfaces. - speech-swift — Apple Silicon MLX companion runtime (model-specific MLX bundles linked above where applicable).
- speech-android — Android SDK consuming on-device LiteRT bundles.
Other LiteRT models in this collection
ASR / Transcription
- Parakeet TDT 0.6B v3 — LiteRT (INT8)
- Nemotron Speech Streaming 0.6B — LiteRT
- Omnilingual ASR CTC 300M — LiteRT
- Omnilingual ASR CTC 300M — LiteRT (INT8)
- Qwen3 ASR 0.6B Encoder — LiteRT (INT8)
VAD / Diarization
License
This bundle inherits the upstream model license (apache-2.0). See the
linked base_model repository for the full terms.