Audio AI had a wild day – 5 major open-source / real-time TTS drops
The audio/TTS space just moved fast. In the last week alone: NVIDIA – PersonaPlex-7B Open-source, full-duplex conversational speech model. Inworld AI – TTS-1.5 Realtime TTS (<250ms), $0.005/min, currently #1 on Artificial Analysis. Flash Labs – Chroma 1.0 First open-source, end-to-end, real-time speech-to-speech model. Alibaba Qwen – Qwen3-TTS Fully open-sourced TTS family: Base, CustomVoice, VoiceDesign. Kyutai Labs – Pocket TTS Runs locally on a laptop. No GPU required. Feels like TTS is hitting the same acceleration moment LLMs had last year. Realtime, open-source, and local is…
Audio AI had a wild day – 5 major open-source / real-time TTS drops launched on January 23, 2026 with 5 votes, #3,400 of 14,584 launches that month and more than 75% of that year's launches.
What it does
Worlds first open-source real-time end-to-end spoken dialogue model with personalized voice cloning. - FlashLabs-AI-Corp/FlashLabs-Chroma
In the maker’s words, at launch
The audio/TTS space just moved fast. In the last week alone: NVIDIA – PersonaPlex-7B Open-source, full-duplex conversational speech model. Inworld AI – TTS-1.5 Realtime TTS (<250ms), $0.005/min, currently #1 on Artificial Analysis. Flash Labs – Chroma 1.0 First open-source, end-to-end, real-time…
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Inworld TTS2025 · inworld.ai · ▲318Hey HN, this is Igor, one of the engineers behind Inworld Runtime, which we're releasing today in public preview. We built it to solve the common problem we and our customers had: engineers spend more time on AI ops and plumbing than on actual feature development. This was often due to the challenge of using Python for I/O-bound, high-concurrency workloads and complexity maintaining pipelines with streams that use always-changing ML models. Our solution is a high-performance runtime written in C++ with the core idea of defining AI logic as graphs. For instance, a basic voice-to-voice…
Kitten TTS – 25MB CPU-Only, Open-Source TTS Model2025 · github.com · ▲1,003Kitten TTS is an open-source series of tiny and expressive text-to-speech models for on-device applications. We are excited to launch a preview of our smallest model, which is less than 25 MB. This model has 15M parameters. This release supports English text-to-speech applications in eight voices: four male and four female. The model is quantized to int8 + fp16, and it uses onnx for runtime. The model is designed to run literally anywhere eg. raspberry pi, low-end smartphones, wearables, browsers etc. No GPU required! We're releasing this to give early users a sense of the latency and voices…
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