Fix OutOfMemoryError During 4x RealESRGAN 4K Upscaling in ComfyUI
Passing a full 1024×1024 image into a non-tiled upscale node attempts to allocate multi-gigabyte intermediate feature maps for a 4096×4096 tensor while the diffusion model is still sitting in VRAM. Unload the diffusion checkpoint first and use tiled upscaling (512×512 tiles with 32px overlap) so peak VRAM stays under 1.5 GB.
1. Exact Terminal Error Signature & Stack Trace
If your standalone ComfyUI, Ollama, or Python terminal outputs the following error on Windows 10/11 x64 or Linux x64:
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB during ImageUpscaleWithModel (RealESRGAN_x4plus.pth, input 1024x1024 -> output 4096x4096)2. Root Cause in Standalone Python, ComfyUI, or Ollama
[Verified] Even though the `RealESRGAN_x4plus` weight file is only ~64 MB on disk, expanding a 1024×1024 image 4x to 4096×4096 (16.7 megapixels) creates massive intermediate convolutional activation tensors. If the 6.8 GB FLUX transformer is still resident in VRAM, an 8 GB or 12 GB GPU runs out of contiguous memory.
3. Manual CLI Fix for Standalone Users (100% Free Utility)
Run the following commands in your terminal or update your launch configuration to resolve the issue immediately in a standalone installation:
# 1. In ComfyUI, use a Tiled Upscale node with tile_size=512, overlap=32 instead of full-frame upscaling.
# 2. Free diffusion weights before running a standalone 4K upscale pass:
curl -X POST http://127.0.0.1:8188/free -H 'Content-Type: application/json' -d '{"unload_models": true, "free_memory": true}'
# 3. Enable --fp16-vae and tiled VAEDecode if combining latent upscale with pixel upscale.4. How Logen 1.4.0 Prevents This Error Automatically
Logen Pro (£49 one-time license) includes a dedicated `esrgan_upscale` 4x pipeline configured with automatic memory management and tiled inference. On our validated NVIDIA RTX A2000 12 GB workstation, Logen 1.4.0 upscales a 1024×1024 render to 4096×4096 (4K) in ~4.2 seconds (`[Verified Measured]`) without overflowing VRAM.
Supported platforms: Windows 10/11 x64 (Logen-1.4.0-Setup.exe) and Linux x64 (Logen-1.4.0.AppImage, Logen-1.4.0-amd64.deb). macOS is not supported.
5. Check Your GPU & Model Memory Headroom
Calculate Exact Dedicated VRAM Headroom on Windows 10/11 & Linux x64
Select your NVIDIA graphics card, diffusion model, operating system, and target resolution to compute deterministic peak VRAM usage before you download weights.
Formula: Dedicated_VRAM (12.0 GB) – [Weights (6.8 GB) + Encoder (1.2 GB) + VAE Buffer (0.9 GB) + OS Reserve (1.5 GB)] = +1.60 GB available headroom.
6. Troubleshooting FAQ: Fix OutOfMemoryError During 4x RealESRGAN 4K Upscaling in ComfyUI
Why does a 64 MB RealESRGAN model use several gigabytes of VRAM?
Model weight size is separate from activation memory. Processing a 1024×1024 image into 4096×4096 requires deep intermediate feature maps across 64 channels per pixel unless the image is split into 512×512 tiles.
Does tiled RealESRGAN upscaling leave visible seams on 4K images?
No, provided the tile overlap is set to at least 32 pixels with feathered blending, which smooths tile boundaries seamlessly.
How fast is 4x RealESRGAN 4K upscaling in Logen 1.4.0?
On our physical NVIDIA RTX A2000 12 GB validation workstation, tiled 4x RealESRGAN upscaling from 1024×1024 to 4096×4096 completes in ~4.2 seconds (`[Verified Measured]`).
7. Related Local AI & ComfyUI Error Guides
- Fix torch.cuda.OutOfMemoryError in ComfyUI on 8GB and 12GB NVIDIA GPUs (VRAM & OOM)
- Fix Prompt Outputs Failed Validation: DualCLIPLoader / VAELoader Not Found in ComfyUI (Missing Nodes & Checkpoints)
- Fix AssertionError: Torch Not Compiled with CUDA Enabled on Windows 10/11 (Python & CUDA Environment)
- Fix CUDA Out of Memory When Running Ollama and ComfyUI Together (VRAM & OOM)
- Fix Cannot Import ComfyUI-GGUF Module: No Module Named 'gguf' (Missing Nodes & Checkpoints)
- Fix Windows 10/11 WDDM Shared GPU Memory Slowdown (Why FLUX Drops from 25s to 4 Minutes) (VRAM & OOM)
- Fix Error: connect ECONNREFUSED 127.0.0.1:11434 (WinError 10061) in Local AI Apps (Ollama & Background Services)
- Fix Black Image or NaN Tensor Output When Decoding FLUX VAE in ComfyUI (VAE & Precision Errors)
- Fix dlopen(): error loading libfuse.so.2 When Launching AppImage on Ubuntu 22.04 / 24.04 (Linux Desktop & Packaging)
Checking hardware compatibility? Browse the Local AI GPU & VRAM Compatibility Index or explore Logen 1.4.0 Desktop Studio.
Generate with FLUX.1-schnell, FLUX.2 [klein] 4B & Z-Image-Turbo in a self-healing desktop studio.
Logen 1.4.0 manages ComfyUI and Ollama automatically on your NVIDIA GPU with zero monthly fees.