低显存优化方案详解
DiffSynth-Engine提供了三种降低显存需求的方法：
- CPU offload技术：在FLUX模型代码中设置
offload_mode="sequential_cpu_offload"可将23GB显存需求降至4GB - 量化模式选择：支持FP8/INT8等量化精度，如q8_0(7-12GB)或q4_k_s(更低)
- parameterization：降低分辨率(width/height)、减少num_inference_steps等
具体操作示例：修改FLUX管道的初始化参数即可生效：
pipe = FluxImagePipeline.from_pretrained(config, offload_mode="sequential_cpu_offload", quant="q4_k_s").eval()
需注意：低显存模式会延长20-50%生成时间，建议根据任务平衡速度和质量。
This answer comes from the articleDiffSynth-Engine: Open Source Engine for Low-Existing Deployments of FLUX, Wan 2.1The
May not be reproduced without permission:AI productivity tools " 如何减少DiffSynth-Engine运行时的显存占用？
English 
简体中文 
日本語 
Deutsch 
Português do Brasil