← ImageLoRA

How to train an SDXL LoRA

Which trainers support SDXL, how much VRAM you need, and settings that work. Every row links to its source.

Trainer support

VRAM

low-VRAM friendly with gradient checkpointing, 8-bit optimizer, cached latents (exact GB unknown)

Known-good settings

• Gradient checkpointing
• 8-bit optimizer
• Cache latents
• OneTrainer: 'compile' + int8 quant on RTX 20xx+

General tips

• Gated Hugging Face models: click 'Agree and access' on each model page, or you'll get 403 errors
• Steps scale with dataset size (steps = epochs x images at batch 1)
• A safe start: LoKr with auto rank (~64), batch/grad accumulation 4

Where to rent a GPU

See cheapest GPU to train a LoRA (RunPod, Vast.ai).

Sources

• www.reddit.com/r/StableDiffusion/comments/1vrkd5x/which_plat
• github.com/ostris/ai-toolkit#readme
• github.com/kohya-ss/sd-scripts#readme
• github.com/bghira/SimpleTuner#readme

Data updated 2026-10-20. RunPod and Vast.ai links are referral links. unknown = no data yet. · Raw data (JSON) · llms.txt