The results of flux_minimal_inference are much worse than webui forge

When I fixed the seed, there was a big gap between the image obtained using flux_minimal_inference.py inference and the image obtained using webui forge. The quality of the image obtained by flux_minimal_inference.py was lower than that of forge. What is the reason? I am training flux. When lora is used, the image obtained by sample may also be of low quality. The machine used both times is the same

This is the script I run. In flux_minimal_inference.py I set both target_height and target_width to 512
`python ./flux_minimal_inference.py \
--ckpt_path=$pretrained_model_name_or_path \
--clip_l=$clip_l \
--t5xxl=$t5xxl \
--ae=$ae \
--prompt="coffee table,pendant lamp,l-shaped sofa,lazy sofa" \
--output_dir=$output_dir \
--flux_dtype=fp8 \
--seed=1 \
--steps=20 \
--guidance=3.5 \
--cfg_scale=1.0 \
--offload`

The results obtained are as follows

Below is the result I got in forge

Start with flux_minimal_inference.py and reproduce the reported command using the fixed seed, 512x512 dimensions, and listed model inputs. Compare its settings and output against the webui forge run, then trace the inference differences. Done means identifying the cause of the quality gap and documenting a reproducible correction or limitation.

Written by the indexing model from the issue text.