ladparis/Z-Image-Turbo-LiteRT-iOS

Z-Image-Turbo — LiteRT bundle for Mirage iOS

Repackaged from litert-community/Z-Image-Turbo-LiteRT (Apache-2.0, converted from Tongyi-MAI/Z-Image-Turbo) with the host-side tensors required to run the full text-to-image pipeline on device:

File	Role
qwen_enc.tflite	Qwen3-4B text encoder (penultimate hidden state)
z_embx.tflite / z_refx.tflite	image patch embed + noise refiner
z_embc.tflite / z_refc.tflite	caption embed + context refiner
zc_main0..5.tflite	30 S3-DiT layers, 5 per chunk
zc_final.tflite	final adaLN + projection
zvae.tflite	VAE decoder
host_tensors.safetensors	embed_tokens (fp32), t_embedder MLP, cap_pad_token, x_pad_token
tokenizer.json	Qwen2 BPE tokenizer

All graphs are INTEGER-int8, fixed 256×256 output, 64-token prompt budget. The host loop (RoPE, adaLN timestep embedding, pad masking, x/cap concat, flow-match Euler, VAE denorm latents / 0.3611 + 0.1159) runs in app code.

License: Apache-2.0 (inherited from Z-Image-Turbo).