ComfyUI Low-VRAM Setup (12GB)

Overview

Most isometric asset failures on consumer GPUs are setup failures, not prompt failures. This skill gives a deterministic, low-VRAM-safe SDXL configuration so generations are reproducible and never OOM on a 12GB card.

When to Use

• Setting up ComfyUI on an RTX 3060 / 12GB or similar.
• Generations randomly crash, stall, or produce inconsistent output.
• You need reproducible results across a whole tile set.

Process

1. Launch ComfyUI with low-VRAM flags: --lowvram (or --medvram-sdxl) and --use-split-cross-attention.
2. Use one SDXL checkpoint for the whole project (e.g. juggernautXL). Never mix checkpoints mid-set.
3. Set the sampler to DPM++ 2M Karras, 30 steps, CFG 6.5. Keep these FIXED for every asset.
4. Load the matching SDXL VAE explicitly (sdxl_vae) - do not rely on baked VAE.
5. FIX the seed for a tile set. A changing seed is the #1 cause of mismatched assets.
6. Generate at 1024x1024, then downscale - do not generate above VRAM budget.
7. Save the workflow JSON so the exact graph is reproducible and shareable.

python main.py --lowvram --use-split-cross-attention

Rationalizations (Stop Lying to Yourself)

Excuse	Reality
"I have enough VRAM, I will skip the flags"	One LoRA stack later you OOM mid-batch and lose the seed. Set flags up front.
"Changing the seed makes assets more varied"	Varied = inconsistent. A tile set needs the SAME seed and settings.

Red Flags - STOP if you catch yourself:

• Mixing checkpoints between assets in the same set.
• Letting the seed randomize across a tile set.
• Generating at 1536+ then wondering why it crashes.

Verification

You are NOT done until every box is checked:

• ComfyUI launches with low-VRAM flags and does not OOM on a full batch.
• Sampler, steps, CFG, VAE and seed are documented and fixed.
• The workflow JSON is saved and re-loads identically.