KittenTTS (KittenML) is the lightweight English "flash" tier: a 25–80 MB ONNX model with 8 preset voices that runs realtime on any CPU — no torch, no CUDA, no GPU of any kind. Use it when you just need quick English narration (voiceovers, demo reads, short phrases) with no reference sample.

• English-only content where speed and a tiny install matter more than cloning.
• Machines with no usable GPU.

The trade-off against OmniVoice: no voice cloning, English only — but a much faster and much smaller install.

pip install kittentts

Then select the engine via Model Catalogue → Engines or OMNIVOICE_TTS_BACKEND=kittentts.

Eight preset voices, four male/female pairs:

expr-voice-2-m  expr-voice-2-f   (default: expr-voice-2-f)
expr-voice-3-m  expr-voice-3-f
expr-voice-4-m  expr-voice-4-f
expr-voice-5-m  expr-voice-5-f

An unknown voice id logs an info message and falls back to the default.

The ~80 MB model downloads from HuggingFace on first use (retried once on a flaky connection). See downloading-models.md.

• Output is 24 kHz mono.
• CPU-only by design — the ONNX graph has no CUDA/MPS path.
• Non-English language values are ignored with a log line pointing at OmniVoice; reference audio is likewise ignored (no cloning).
• Long-input hardening (#1173): the shipped ONNX graph has a hard 512-token cap, and phonemization can expand text massively (digits especially). VoiceStudio pre-measures every chunk with the model's own tokenizer and splits oversized chunks at word boundaries, so long or digit-heavy inputs no longer abort inside onnxruntime with an opaque "invalid expand shape" error.

• English only; no cloning, no voice design, no emotion controls (see expressive-speech.md).
• Preset voices only — speed is the one knob.

• Engine unavailable: pip install kittentts into VoiceStudio's Python environment and restart.
• Other issues: install/troubleshooting.md.

See also: benchmarks.md, disk usage.