error occurs because the GPU memory allocator in your 13th Gen Intel iGPU (Intel Xe Graphics) cannot handle the large memory request made by Stable Diffusion (SD.Next using OpenVINO). Specifically:

• Requested: 8,589,934,592 bytes (~8GB)

• Max allowed per allocation: 4,294,959,104 bytes (~4GB)

This is a hardware limitation of integrated Intel GPUs — they typically have a maximum buffer allocation size around 4GB, even if more shared memory is available overall.

🔧 How to Fix It

Here are ways to address this:

✅ 1. Reduce Batch Size

In the SD.Next interface:

• Find the Batch size setting (not to be confused with "Batch count")

• Set Batch size = 1 (this will reduce the single memory block size)

This is usually the most effective and easiest fix.

✅ 2. Use Lower Precision (FP16)

OpenVINO can support FP16 (half precision), which drastically reduces memory usage.

If you are using a model in FP32, try:

• Converting your model to FP16

• Or downloading an FP16 version of the model (if available)

Some UIs (like SD.Next, ComfyUI, or WebUI) allow selecting FP16 models directly or during import.

✅ 3. Use a Smaller Model

Stable Diffusion 1.5 requires less VRAM than SD 2.1 or SDXL.

Try:

• Switching from SDXL → SD 1.5

• Or using Lite versions of models if available (like "v1.5-pruned-emaonly" or "tiny" models)

✅ 4. Use CPU Instead (as fallback)

If the GPU is not sufficient, you can:

• Select OpenVINO [CPU] backend

• It will be slower but more compatible

Use this as a last resort if GPU execution isn't viable.

⚠️ Notes

• This limitation is not something that can be bypassed by modifying system settings — it's enforced by the Intel OpenVINO GPU runtime and the GPU hardware.

• SDXL and models with high-resolution pipelines or large attention layers are more likely to trigger this problem.

app: sdnext
updated: 2025-06-19
hash: 7fc7797a
url: https://github.com/vladmandic/sdnext/tree/dev
arch: x86_64
cpu: x86_64
system: Linux
release: 6.11.0-26-generic
python: 3.12.3
2.7.1+xpu
2.7.1+xpu
ram: free:85.83 used:8.14 total:93.97

xformers: 
diffusers: 0.34.0.dev0
transformers: 4.52.4
active: xpu
dtype: torch.bfloat16
vae: torch.bfloat16
unet: torch.bfloat16
base: model.safetensors
refiner: None
vae: Automatic
te: Default
unet: Default