Kani TTS 2

Kani TTS 2 TTS

An ultra-lightweight 400M English model that runs in just 3GB of VRAM at a 0.2 real-time factor.

Inscríbete límite de 5. 000 caracteres

Incluír o texto en etiquetas SSML para un control preciso:

<speak><prosody rate="slow">Slow speech</prosody></speak>

Etiquetas que o modelo escollido entende - prema para deixar unha no texto onde ocorre:

Este modelo le texto simple, polo que se ignoran as etiquetas inline. Para emocións baseadas en etiquetas, cambie a un modelo expresivo como Orpheus ou Bark.

Definir pronunciacións personalizadas (palabra = pronunciación):

-12 +12
0.5x 2.0x
Libre con Piper, VITS, MeloTTS
O son xerado aparecerá aquí. Escolla un modelo, introduza o texto e prema Xerar.
O son xerou correctamente
0:00
Obter o son Obter.srt A ligazón caduca en 24 horas
Nivel libre: uso persoal. Licenza comercial desde $5/mes
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Acerca de Kani TTS 2

Kani-TTS-2 by NineNineSix is an ultra-lightweight 400M-parameter text-to-speech model built on a Liquid AI LFM2 backbone with NVIDIA's NanoCodec. It runs in just 3GB of VRAM and generates roughly ten seconds of speech in about two seconds on an A100 — a real-time factor near 0.2. The current public release ships an English-only checkpoint and, unlike its predecessor, does not expose the speaker-embedding hook needed for voice cloning. Its strength is fast, low-cost English generation on modest hardware, which makes it a good fit for quick previews and high-volume English narration. It is released under Apache 2.0 and offered on the free tier.

Mellor para: Fast English generation on low-VRAM hardware, quick previews

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Desenvolvente
NineNineSix
Licenza
Apache 2.0
Tier
free
Velocidade
fast
Clonaxe de voz
Non
Linguas
English
Caracteres máximos
1000

Kani TTS 2 voces

Default

English
Estándar Neutral

Kani TTS 2 TTS - FAQ

It runs in just 3GB of VRAM and produces about ten seconds of speech in roughly two seconds on an A100 — a real-time factor near 0.2 — thanks to its 400M-parameter LFM2 backbone and NanoCodec.

No. The current v2 release removed the public speaker-embedding hook, so cloning is not available. For cloning, use Chatterbox, IndexTTS-2, or GPT-SoVITS.

English only. The public release ships a single English checkpoint; for non-English speech, use a model like Kokoro or MeloTTS.
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