Both OneTrainer and SimpleTuner can train SDXL LoRAs. Here is how they compare, using each project's docs and GitHub activity.
| OneTrainer | SimpleTuner | |
|---|---|---|
| SDXL support | supported | supported |
| GitHub stars | 3247 | 2942 |
| Last commit | 2026-10-19 | 2026-10-20 |
| Latest release | none published | v4.10.1 |
| VRAM (SDXL) | low-VRAM friendly with gradient checkpointing, 8-bit optimizer, cached latents (exact GB unknown) | |
| Overview | GUI + CLI trainer with a broad model list; good VRAM use and speed, but more settings to configure. | bghira's trainer; more powerful (e.g. teacher-student regularization), but the data loader is harder to set up. |
If you want the quickest start with a web UI, pick ai-toolkit. If you already use a script-based trainer's ecosystem, stick with it.
Cheapest 16 GB+ cards (2026-10-20 08:06 UTC) from RunPod and Vast.ai. Prices move constantly; see the live price table.
| GPU | VRAM | RunPod community $/hr | Vast.ai cheapest $/hr |
|---|---|---|---|
| Tesla V100 | 16 GB | $0.19 | $0.08 |
| RTX 3090 | 24 GB | $0.22 | $0.12 |
| RTX 5060 Ti | 16 GB | — | $0.14 |
| Tesla V100S | 32 GB | — | $0.14 |
| RTX A5000 | 24 GB | $0.16 | — |
| RTX A4000 | 16 GB | $0.17 | — |
Both support it. Pick based on workflow (UI vs scripts) and the notes above.
supported
supported
Data updated 2026-10-20. Disclosure: RunPod and Vast.ai links are referral links; ImageLoRA may earn a commission at no cost to you. unknown = no data yet. · Raw data (JSON) · llms.txt