Kokoro-82M (StyleTTS2 + iSTFTNet) exported to Apple's Core AI.aimodel format for iOS 27 and macOS 26. Built for OpenReader iOS, an on-device document reader. Published because the export differs from the community recipe in one way that matters, and because a working Core AI TTS export was hard enough to arrive at that it is worth not repeating. Three fixed-shape bundles with two host steps between them. Kokoro's acoustic graph has exactly one data-dependent length — the duration-to-alignment expansion L = sum(preddur) — so the model is cut where that length appears rather than being made dynamic. Token bucket 128, frame bucket 512 — one pass renders 12.8 s of audio. Fixed buckets are not a…
Open weights
apache-2.0
coreai
English Chatterbox Turbo for OpenReader, with FP16 T3 weights and attention cache, and FP32 T3 intermediate math. S3Gen and the mandatory Perth watermark are the original FP32 exports. Other OpenReader TTS models are unchanged. This is a smaller download, not a claim of all-half arithmetic or realtime speech. Source is resemble-ai/chatterbox at 5de7a54aa4e5e2baadb0182dde554908b48b85c2; weights, tokenizer and official default voice conditioning are ResembleAI/chatterbox-turbo at 749d1c1a46eb10492095d68fbcf55691ccf137cd. The MIT notice is in LICENSE.txt. There are no personal voice recordings. T3's graph takes shared half-weight tensors as inputs. This avoids expanding constant casts during…
Open weights
mit
English Chatterbox Nano conversion for OpenReader and Apple's Core AI runtime. Official weights revision 71ccd1d0081b430592cea481f4307e764e07bc64; Chatterbox source revision 5de7a54aa4e5e2baadb0182dde554908b48b85c2 (nano=True loader). The official default voice, tokenizer, MIT notice and Perth watermark are included. No personal recordings are included. T3 has twelve layers, hidden width 768 and twelve attention heads. Projections, host embeddings, K/V storage and decode attention use FP16. Normalization, residuals, prefill attention and output logits use FP32. There is no per-token palette expansion. Ordinary cache inputs/outputs avoid the large attention errors observed with Core AI…
Open weights
mit
