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PrunaAI releases P-Q-Image-2.1, a six-step LoRA for Qwen-Image-2.1

AIPrunaAI releases P-Q-Image-2.1, a set of v0.2 LoRA adapters that run on Qwen-Image-2.1 in six steps without CFG, with generation up to 6.3× faster. The adapters handle text-to-image generation and single- or multi-image editing with up to three reference images, and the 6-steps-upsampled variant folds prompt-upscaling into the adapter.
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P-Q-Image-2.1 brings Qwen-Image-2.1 generation and editing down to six steps, with no CFG and up to 6.3× faster generation.
🤖 https://modelscope.ai/models/PrunaAI/P-Q-Image-2.1

⚡ Six steps, same workflow: The v0.2 LoRA adapters run on top of Qwen-Image-2.1 while keeping its base pipeline, text encoder, and VAE unchanged.
🖼️ Generate or edit: Use one adapter for text-to-image generation and single- or multi-image editing, with up to three reference images.
✨ Skip the separate prompt-upscaling pass: The 6-steps-upsampled variant incorporates prompt-upscaling benefits into the adapter, reducing end-to-end generation time from a short prompt.
🎛️ Choose the trade-off: Use 6-steps for behavior closer to the base model, or 6-steps-upsampled when prioritizing visual quality from concise prompts.
🛠️ Built for the Qwen stack: Start at 1024 × 1024 and use the matching six-step schedule. Higher resolutions may work, but were outside the adapter’s training coverage.
📜 Qwen Research License Agreement. This is a LoRA adapter, not a standalone model; it requires the Qwen-Image-2.1 base weights.

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Original title: P-Q-Image-2.1 brings Qwen-Image-2.1 generation and editing down to six steps, with no CFG and up to 6.3× faster generation.