# KittenTTS - The Nano TTS Source: https://www.youtube.com/watch?v=YpQWdrfzSzQ Recap page: https://rapidrecap.app/video/YpQWdrfzSzQ Generated: 2026-02-22T15:31:24.607+00:00 --- ## Quick Overview Kitten TTS released an upgrade featuring three new tiny, open-source text-to-speech models (80M, 40M, and 14M parameters), with the smallest quantized version being just 25MB and capable of running on minimal hardware, including directly in a browser or on edge devices without a GPU. **Key Points:** - Kitten TTS released an upgrade with three new models: 80 million (Mini), 40 million (Micro), and 14 million (Nano) parameters. - The smallest model, kitten-tts-nano-0.8-int8 (15M parameters), is only 25MB and optimized to run on CPU/minimal hardware without requiring a GPU. - The models are built on the StyleTTS 2 architecture and offer high-quality voice synthesis with fast inference, optimized for real-time deployment. - The update includes 8 distinct voices (Bella, Jasper, Luna, Bruno, Rosie, Hugo, Kiki, Leo) available across the models, particularly showcased using the 80M Mini model. - Benchmark tests demonstrated fast inference times, with the Nano fp32 model achieving a Real-Time Factor (RTF) of 0.30x for conversational text. - The project is open-source under the Apache-2.0 license and actively maintains a GitHub repository and Discord community for user interaction and support. ![Screenshot at 00:03: The screen displays the title 'Kitten TTS' alongside animated cats, confirming the launch of three new tiny models: 80 million, 40 million, and the smallest at 14 million parameters.](https://ss.rapidrecap.app/screens/YpQWdrfzSzQ/00-00-03.jpg) **Context:** The video announces an upgrade to Kitten TTS, an open-source, lightweight text-to-speech (TTS) system developed by KittenML, emphasizing its focus on creating compact, high-quality models suitable for deployment on resource-constrained devices. The announcement highlights the release of three new model sizes (80M, 40M, 14M parameters) and showcases performance benchmarks and voice quality across these different sizes and quantization levels. ## Detailed Analysis Kitten TTS has been upgraded, introducing three new tiny, open-source TTS models based on the StyleTTS 2 architecture: Mini (80M parameters, 79MB), Micro (40M parameters, 40MB), and Nano (15M parameters, 56MB). Crucially, an 8-bit quantized version of the Nano model (kitten-tts-nano-0.8-int8) achieves a file size of just 25MB, allowing it to run efficiently on CPU or minimal hardware, even within a browser or on mobile devices. The models support 8 pre-made voices (Bella, Jasper, Luna, Bruno, Rosie, Hugo, Kiki, Leo), demonstrated via conversational and technical sentences, showing strong voice quality maintained even in the smallest versions. Benchmarks confirm the models' speed, with the Nano fp32 model achieving an RTF of 0.30x on conversational text, significantly faster than previous architectures. The project is committed to packing frontier intelligence into these tiny models and encourages community engagement via GitHub and Discord. ### New Model Sizes - Three new models launched: 80M (Mini), 40M (Micro), and 14M (Nano) parameters - The smallest quantized model (Nano int8) is 25MB and CPU-optimized. ### Model Features - Ultra-lightweight design - CPU-optimized (no GPU required) - High-quality voices with fast inference - Apache-2.0 license. ### Voice Comparison (Conversational) - Voice 'Bella' tested across all four available sizes (Nano int8, Nano fp32, Micro, Mini) - Nano int8 inference time was 9.23s (RTF 1.20x), while Mini inference was 12.58s (RTF 1.84x). ### Voice Comparison (Technical) - Voice 'Jasper' tested across all four sizes - Nano int8 inference time was 8.94s (RTF 0.84x), while Micro was 0.88s (RTF 0.86x). ### Voice Showcase (Mini Model) - All 8 available voices (Bella, Jasper, Luna, Bruno, Rosie, Hugo, Kiki, Leo) tested on the 80M Mini model - The text used was: "The future of artificial intelligence is incredibly exciting, and I can't wait to see what we build together." ### Performance Benchmarks (Jasper Voice) - Nano int8 (15M params) showed 0.811 RTF - Nano fp32 (15M params) showed 0.299 RTF - Micro (40M params) showed 0.899 RTF - Mini (80M params) showed 1.851 RTF. ![Screenshot at 00:00: Introduction screen displaying the 'Kitten TTS' branding and announcing an upgrade to the super-tiny, expressive open-source models.](https://ss.rapidrecap.app/screens/YpQWdrfzSzQ/00-00-00.jpg) ![Screenshot at 00:13: A screenshot of the KittenML models page on Hugging Face, listing several versions including nano, micro, and mini models with varying parameter counts and formats \(int8, fp32\).](https://ss.rapidrecap.app/screens/YpQWdrfzSzQ/00-00-13.jpg) ![Screenshot at 03:15: A Google Colab notebook environment showing the installation command \(pip install\) and the basic usage code snippet for loading and generating audio with KittenTTS.](https://ss.rapidrecap.app/screens/YpQWdrfzSzQ/00-03-15.jpg) ![Screenshot at 04:00: Code output section comparing the conversational sentence generation performance of four different model sizes \(Nano int8, Nano fp32, Micro, Mini\) using the voice 'Bella'.](https://ss.rapidrecap.app/screens/YpQWdrfzSzQ/00-04-00.jpg) ![Screenshot at 07:43: A Pandas DataFrame displaying benchmark results \(3-run average\) for different models \(Nano int8, Nano fp32, Micro, Mini\) using the voice 'Jasper', showing average inference time, audio duration, and RTF.](https://ss.rapidrecap.app/screens/YpQWdrfzSzQ/00-07-43.jpg)