← ImageLoRA
How to train a FLUX.3 Image Klein LoRA
Which trainers support FLUX.3 Image Klein (BFL), how much VRAM you need, and settings that work. Every row links to its source.
Trainer support
| Trainer | Status |
|---|
| ai-toolkit | supported (day-0, PR #1078 merged Oct 15; fixes Oct 15) |
| OneTrainer | unknown |
| musubi-tuner | unknown |
| kohya sd-scripts | unknown |
| SimpleTuner | supported (Base + distilled klein recipes, 24-144 GB) |
VRAM
SimpleTuner recipes: Base from 24 GB (512px, batch 3) up to 144 GB; distilled klein at 24 GB (768px, batch 1) or 80 GB (1024px, batch 4)
Known-good settings
- Open weights, gated on Hugging Face: click 'Agree and access' on the model page or downloads fail with 403
- Mixed early reception; watch for anatomy issues
- Base model sampling: ~50 steps, CFG 3.5
- LoRA strength ~1.3 at inference
- Character LoRAs come out weak at the default rank 16/32; go higher
- SimpleTuner recipes: rank-32 LoRA, LR 1e-4, REPA; distilled klein auto-loads a published training-assistant LoRA (strength 1.0 in training, 0.0 at validation; disable_assistant_lora to turn off)
- ai-toolkit edit training with several control images used only one until a fix on Oct 17; update before training edit LoRAs
- A FLUX.2 dataset and recipe carried over unchanged doesn't work well; long upsampled prompts with JSON bounding boxes at ~2 MP sample better
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
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Data updated 2026-10-20. RunPod and Vast.ai links are referral links. unknown = no data yet. · Raw data (JSON) · llms.txt