The fastest way to get this model running locally is via Docker.

Follow the step-by-step instructions below.

1-click setup: the app automatically fetches the large weight files.

The automated installation script takes care of everything by tailoring the setup perfectly to your system specs.

📊 File Hash: de58e1f94561227ecdee9d6b73732331 — Last update: 2026-06-24 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: 32 GB or higher for smooth 32k context lengths Disk Space: free: 80 GB on system drive for scratch space Graphics: TensorRT-LLM / vLLM inference engine compatible chip

The z_image_turbo model leverages a deep residual architecture to deliver real‑time image generation with unprecedented speed. It supports up to 4K resolution while maintaining high fidelity through advanced denoising techniques. The model’s parameter count of 1.5 B enables deployment on consumer GPUs without sacrificing quality. A dedicated tensor core optimization reduces inference latency to under 50 ms per image. The integrated adaptive scaling ensures consistent performance across diverse input styles and resolutions.

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