Price floor Every GPU at least 30% below the market median — re-checked against the marketplace weekly.

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Template · Training & fine-tuning · CUDA 12.6

Run Kohya LoRA training on a cloud GPU, in 30 seconds

Train SDXL and Flux image LoRAs in a browser GUI — dataset in, .safetensors out. Kohya's GUI is the standard trainer for Stable Diffusion, SDXL and Flux LoRAs: dataset prep, captioning helpers, bucketed resolutions and a browser UI over the sd-scripts. Twenty to forty images in, a .safetensors LoRA out, usually within an hour on a 4090. From $0.052/hr on an interruptible RTX 3090.

Running in ~30 s

Pre-cached image, ports mapped, TLS terminated — the stack is working before you finish reading this.

Template is free

You pay the GPU price only: Kohya's GUI on a RTX 3090 is $0.104/hr on-demand, $0.052/hr interruptible, billed per second.

Volumes for state

Models, datasets and outputs live on a $0.08/GB/mo volume; the instance stays disposable.

Private by default

Dedicated GPU, encrypted disk, crypto payments, no KYC, no stored IPs — Jupyter and SSH behind your own credentials.

Best GPUs for Kohya's GUI

Three price points that run this template well — Good, Better, Best. Every model in the catalogue works; these are the value picks.

TierGPUVRAMOn-demandInterruptibleWhy this cardAction
GoodRTX 309024 GB$0.104$0.05224 GB at the lowest rate for SDXL LoRAs.Deploy
BetterRTX 409024 GB$0.262$0.131The community default: SDXL and Flux LoRAs in 30–60 minutes.Deploy
BestRTX 509032 GB$0.318$0.15932 GB for Flux full-precision training and larger batch sizes.Deploy

Need more VRAM? The full catalogue lists all 76 models with live availability; the VRAM guide sizes models to cards.

Deploy Kohya's GUI from the console, CLI or API

Pick the template in the console deploy bar, or script it:

  • Console — filter by GPU, choose Kohya's GUI in the template picker, set disk and env, deploy.
  • CLIpip install powergpu, then the command on the right. CLI reference.
  • APIPOST /v1/instances with "template": "kohya-s-gui". REST reference.
  • Own image — any OCI reference works too; we inject the NVIDIA runtime. Template docs.
deploy — kohya-s-gui
$ powergpu launch --gpu rtx-3090 --template kohya-s-gui \
    --disk 100 --volume models:/workspace/models
 instance i-7a41c0e2 running (27.9s)
# Kohya's GUI · RTX 3090 · $0.104/hr · per second
# https://i-7a41c0e2.powergpu.io:8888 (TLS)
$ powergpu stop i-7a41c0e2   # billing ends this second

What is inside the Kohya's GUI template

Imagepowergpu/kohyas-gui
CUDACUDA 12.6
AccessSSH shell · JupyterLab on a mapped port
CategoryTraining & fine-tuning
StorageInstance NVMe disk (sized at deploy) + optional network volumes
BillingGPU price only, per second — no template fee, no setup fee

Other training & fine-tuning templates

Kohya's GUI on a cloud GPU: FAQ

Environment variables, ports and custom images are covered in the template docs.

How much does it cost to run Kohya's GUI on a cloud GPU?

Only the GPU price — the template is free. From $0.052/hr on an interruptible RTX 3090, $0.104/hr on-demand on a RTX 3090. Billing is per second, so an hour of tinkering costs an hour, not a day. Storage is $0.08/GB/month.

How long does Kohya's GUI take to start?

About 30 seconds from the deploy click: the image is pre-cached on hosts, ports are mapped and TLS is terminated for you. Restarting a stopped instance is faster, and your disk is exactly as you left it.

Can I keep my models and outputs between sessions?

Yes — attach a volume at deploy. Everything on the volume survives instance destruction and mounts on the next instance in the region in seconds, at $0.08/GB/month. The instance disk itself survives stop/start but not destroy.

How much does a style LoRA cost to train?

A typical 30-image SDXL LoRA at 1,500 steps takes 30–45 minutes on an RTX 4090 — well under a dollar on interruptible pricing.

Deploy your first GPU in under a minute

Top up in crypto, benchmark us against your current provider. Per-second billing, fixed prices ≥ 30% below market — cancel by just stopping the instance.