Both kohya sd-scripts and SimpleTuner can train FLUX.1 LoRAs. Here is how they compare, using each project's docs and GitHub activity.
| kohya sd-scripts | SimpleTuner | |
|---|---|---|
| FLUX.1 support | supported | supported |
| GitHub stars | 7242 | 2942 |
| Last commit | 2026-10-20 | 2026-10-20 |
| Latest release | v0.12.2 | v4.10.1 |
| VRAM (FLUX.1) | ai-toolkit ships a 24GB example config (train_lora_flux_24gb.yaml) | |
| Overview | The long-standing kohya training scripts (also used by the kohya_ss GUI); strongest for SD1.5/SDXL-era models. | 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 24 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 |
|---|---|---|---|
| RTX 3090 | 24 GB | $0.22 | $0.12 |
| Tesla V100S | 32 GB | — | $0.14 |
| RTX A5000 | 24 GB | $0.16 | — |
| RTX PRO 4000 | 24 GB | $0.50 | $0.26 |
| RTX 3090 Ti | 24 GB | $0.27 | — |
| RTX A6000 | 48 GB | $0.33 | $0.40 |
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