Both OneTrainer and kohya sd-scripts can train SDXL LoRAs. Here is how they compare, using each project's docs and GitHub activity.
| OneTrainer | kohya sd-scripts | |
|---|---|---|
| SDXL support | supported | supported |
| GitHub stars | 3243 | 7244 |
| Last commit | 2026-10-16 | 2026-09-24 |
| Latest release | none published | v0.12.0 |
| 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; users report good VRAM use and speed but more settings to configure. | The long-standing kohya training scripts (also used by the kohya_ss GUI); strongest for SD1.5/SDXL-era models. |
If you want the quickest start with a web UI, ai-toolkit is the usual community pick; choose a script-based trainer if you already use its ecosystem. We don't have a sourced head-to-head quality benchmark for SDXL between these two, so treat any "better results" claim as unknown.
Cheapest 16 GB+ cards (2026-10-16 14:43 UTC) from RunPod and Vast.ai. Prices move constantly; see the live price table.
| GPU | VRAM | RunPod community $/hr | Vast.ai cheapest $/hr |
|---|---|---|---|
| RTX A4000 | 16 GB | $0.17 | $0.09 |
| Tesla V100 | 16 GB | $0.19 | $0.10 |
| RTX 3090 | 24 GB | $0.22 | $0.12 |
| RTX 5060 Ti | 16 GB | — | $0.12 |
| RTX 5070 Ti | 16 GB | — | $0.12 |
| RTX A5000 | 24 GB | $0.16 | — |
Both support it. There is no sourced quality benchmark between them for this model yet; pick based on workflow (UI vs scripts) and the notes above.
supported
supported
Data updated 2026-10-16. Disclosure: RunPod and Vast.ai links are referral links; ImageLoRA may earn a commission at no cost to you. unknown = not yet verified from a source.