Images in Forge created with Flux (dev and schnell) turn grey or black last second

[Leportan]

I know this has been asked before in other places but I couldn't find a solution anywhere. Am using an RTX4000 (8GB VRam) and have at least 64GB DDR4 Ram.
The images are amazing but then turn grey/black last second. Is there a fix for this issue yet? I tried it even with the 3 different versions of Flux with the same black image as a result.

Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug  1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Version: f2.0.1v1.10.1-previous-561-g82eb7566
Commit hash: 82eb7566172934d2edefc536afe2499b9593999f
Launching Web UI with arguments:
Total VRAM 8192 MB, total RAM 65414 MB
pytorch version: 2.3.1+cu121
Set vram state to: NORMAL_VRAM
Device: cuda:0 Quadro RTX 4000 : native
Hint: your device supports --cuda-malloc for potential speed improvements.
VAE dtype preferences: [torch.float32] -> torch.float32
CUDA Using Stream: False
D:\Forge (Flux)\system\python\lib\site-packages\transformers\utils\hub.py:127: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead.
  warnings.warn(
Using pytorch cross attention
Using pytorch attention for VAE
ControlNet preprocessor location: D:\Forge (Flux)\webui\models\ControlNetPreprocessor
Loading additional modules ... done.
2024-10-11 15:47:54,153 - ControlNet - INFO - ControlNet UI callback registered.
Model selected: {'checkpoint_info': {'filename': 'D:\\Forge (Flux)\\webui\\models\\Stable-diffusion\\flux1-dev.safetensors', 'hash': 'b04b3ba1'}, 'additional_modules': ['D:\\Forge (Flux)\\webui\\models\\text_encoder\\clip_l.safetensors', 'D:\\Forge (Flux)\\webui\\models\\VAE\\diffusion_pytorch_model.safetensors', 'D:\\Forge (Flux)\\webui\\models\\text_encoder\\t5xxl_fp16.safetensors'], 'unet_storage_dtype': None}
Using online LoRAs in FP16: False
Running on local URL:  http://127.0.0.1:7860

To create a public link, set `share=True` in `launch()`.
Startup time: 29.8s (prepare environment: 5.1s, import torch: 12.5s, initialize shared: 0.3s, other imports: 1.0s, load scripts: 2.4s, initialize google blockly: 4.8s, create ui: 2.3s, gradio launch: 1.2s).
Environment vars changed: {'stream': False, 'inference_memory': 1024.0, 'pin_shared_memory': False}
[GPU Setting] You will use 87.50% GPU memory (7167.00 MB) to load weights, and use 12.50% GPU memory (1024.00 MB) to do matrix computation.
Loading Model: {'checkpoint_info': {'filename': 'D:\\Forge (Flux)\\webui\\models\\Stable-diffusion\\flux1-dev.safetensors', 'hash': 'b04b3ba1'}, 'additional_modules': ['D:\\Forge (Flux)\\webui\\models\\text_encoder\\clip_l.safetensors', 'D:\\Forge (Flux)\\webui\\models\\VAE\\diffusion_pytorch_model.safetensors', 'D:\\Forge (Flux)\\webui\\models\\text_encoder\\t5xxl_fp16.safetensors'], 'unet_storage_dtype': None}
[Unload] Trying to free all memory for cuda:0 with 0 models keep loaded ... Done.
StateDict Keys: {'transformer': 780, 'vae': 244, 'text_encoder': 196, 'text_encoder_2': 220, 'ignore': 0}
Using Default T5 Data Type: torch.float16
Working with z of shape (1, 16, 32, 32) = 16384 dimensions.
IntegratedAutoencoderKL Missing: ['encoder.down.0.block.0.norm1.weight', 'encoder.down.0.block.0.norm1.bias', 'encoder.down.0.block.0.conv1.weight', 'encoder.down.0.block.0.conv1.bias', 'encoder.down.0.block.0.norm2.weight', 'encoder.down.0.block.0.norm2.bias', 'encoder.down.0.block.0.conv2.weight', 'encoder.down.0.block.0.conv2.bias', 'encoder.down.0.block.1.norm1.weight', 'encoder.down.0.block.1.norm1.bias', 'encoder.down.0.block.1.conv1.weight', 'encoder.down.0.block.1.conv1.bias', 'encoder.down.0.block.1.norm2.weight', 'encoder.down.0.block.1.norm2.bias', 'encoder.down.0.block.1.conv2.weight', 'encoder.down.0.block.1.conv2.bias', 'encoder.down.0.downsample.conv.weight', 'encoder.down.0.downsample.conv.bias', 'encoder.down.1.block.0.norm1.weight', 'encoder.down.1.block.0.norm1.bias', 'encoder.down.1.block.0.conv1.weight', 'encoder.down.1.block.0.conv1.bias', 'encoder.down.1.block.0.norm2.weight', 'encoder.down.1.block.0.norm2.bias', 'encoder.down.1.block.0.conv2.weight', 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K-Model Created: {'storage_dtype': torch.bfloat16, 'computation_dtype': torch.float16}
Model loaded in 0.8s (unload existing model: 0.2s, forge model load: 0.6s).
Skipping unconditional conditioning when CFG = 1. Negative Prompts are ignored.
[Unload] Trying to free 13464.34 MB for cuda:0 with 0 models keep loaded ... Done.
[Memory Management] Target: JointTextEncoder, Free GPU: 7123.00 MB, Model Require: 9569.49 MB, Previously Loaded: 0.00 MB, Inference Require: 1024.00 MB, Remaining: -3470.49 MB, CPU Swap Loaded (blocked method): 4902.00 MB, GPU Loaded: 4739.87 MB
Moving model(s) has taken 3.67 seconds
Distilled CFG Scale: 3.5
[Unload] Trying to free 30800.42 MB for cuda:0 with 0 models keep loaded ... Current free memory is 1600.08 MB ... Unload model JointTextEncoder Done.
[Memory Management] Target: KModel, Free GPU: 7081.66 MB, Model Require: 22700.13 MB, Previously Loaded: 0.00 MB, Inference Require: 1024.00 MB, Remaining: -16642.47 MB, CPU Swap Loaded (blocked method): 17946.00 MB, GPU Loaded: 4754.13 MB
Moving model(s) has taken 4.89 seconds
100%|##################################################################################| 20/20 [01:39<00:00,  4.97s/it]
[Unload] Trying to free 8991.55 MB for cuda:0 with 0 models keep loaded ... Current free memory is 2076.00 MB ... Unload model KModel Done.
[Memory Management] Target: IntegratedAutoencoderKL, Free GPU: 7060.69 MB, Model Require: 319.75 MB, Previously Loaded: 0.00 MB, Inference Require: 1024.00 MB, Remaining: 5716.94 MB, All loaded to GPU.
Moving model(s) has taken 1.39 seconds
Total progress: 100%|██████████████████████████████████████████████████████████████████| 20/20 [01:27<00:00,  4.37s/it]
Total progress: 100%|██████████████████████████████████████████████████████████████████| 20/20 [01:27<00:00,  4.43s/it]

[abzaloff]

Try changing the VAE from here. Download the ae.safetensors file
https://huggingface.co/black-forest-labs/FLUX.1-dev/tree/main
P.S. with 8GB of video memory, I would recommend that you use the NF4 model. They do not need encoders and VAE

[Leportan]

Thank you so much for the reply. This solved it. (For others reading: I put ae.safetensors into the models/VAE folder and selected it in Forge in the top bar (VAE / Text Encoder) alongside the other models.)