Running in ~30 s
Pre-cached image, ports mapped, TLS terminated — the stack is working before you finish reading this.
Template · Training & fine-tuning · CUDA 12.9
Run AI Toolkit (Ostris) on a cloud GPU, in 30 seconds
The AI-Toolkit trainer for Flux and diffusion models, with a web UI. Ostris' AI Toolkit is the trainer of choice for Flux and newer diffusion models: LoRA training with a clean YAML, a web UI for monitoring, and support for the latest model releases before other tools catch up. From $0.131/hr on an interruptible RTX 4090.
Template is free
You pay the GPU price only: Ostris AI Toolkit on a RTX 4090 is $0.262/hr on-demand, $0.131/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 Ostris AI Toolkit
Three price points that run this template well — Good, Better, Best. Every model in the catalogue works; these are the value picks.
| Tier | GPU | VRAM | On-demand | Interruptible | Why this card | Action |
|---|---|---|---|---|---|---|
| Good | RTX 4090 | 24 GB | $0.262 | $0.131 | Runs Flux dev LoRA training with the low-VRAM flag. | Deploy |
| Better | RTX 5090 | 32 GB | $0.318 | $0.159 | 32 GB of headroom for larger resolutions. | Deploy |
| Best | RTX PRO 6000 WS | 96 GB | $1.097 | $0.548 | 96 GB for full fine-tunes of diffusion models. | Deploy |
Need more VRAM? The full catalogue lists all 76 models with live availability; the VRAM guide sizes models to cards.
Deploy Ostris AI Toolkit from the console, CLI or API
Pick the template in the console deploy bar, or script it:
- Console — filter by GPU, choose Ostris AI Toolkit in the template picker, set disk and env, deploy.
- CLI — pip install powergpu, then the command on the right. CLI reference.
- API — POST /v1/instances with "template": "ostris-ai-toolkit". REST reference.
- Own image — any OCI reference works too; we inject the NVIDIA runtime. Template docs.
$ powergpu launch --gpu rtx-4090 --template ostris-ai-toolkit \
--disk 100 --volume models:/workspace/models
✓ instance i-7a41c0e2 running (27.9s)
# Ostris AI Toolkit · RTX 4090 · $0.262/hr · per second
# https://i-7a41c0e2.powergpu.io:8888 (TLS)
$ powergpu stop i-7a41c0e2 # billing ends this secondWhat is inside the Ostris AI Toolkit template
| Image | powergpu/ostris-ai-toolkit |
|---|---|
| CUDA | CUDA 12.9 |
| Access | SSH shell · JupyterLab on a mapped port |
| Category | Training & fine-tuning |
| Storage | Instance NVMe disk (sized at deploy) + optional network volumes |
| Billing | GPU price only, per second — no template fee, no setup fee |
Other training & fine-tuning templates
Axolotl — Fine Tuning on a cloud GPU — Fine-tune Llama, Qwen or Mistral from one YAML — LoRA, QLoRA and multi-GPU FSDP.
Unsloth Studio on a cloud GPU — 2× faster, lower-VRAM fine-tuning — Unsloth kernels with a notebook workflow.
Kohya's GUI on a cloud GPU — Train SDXL and Flux image LoRAs in a browser GUI — dataset in, .safetensors out.
Flux Gym on a cloud GPU — A dead-simple UI for training Flux LoRAs, built on the Kohya scripts.- All 37 templates
Ostris AI Toolkit on a cloud GPU: FAQ
Environment variables, ports and custom images are covered in the template docs.
How much does it cost to run Ostris AI Toolkit on a cloud GPU?
Only the GPU price — the template is free. From $0.131/hr on an interruptible RTX 4090, $0.262/hr on-demand on a RTX 4090. Billing is per second, so an hour of tinkering costs an hour, not a day. Storage is $0.08/GB/month.
How long does Ostris AI Toolkit 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.
Can I train on a mounted dataset volume?
Yes — point the config's dataset path at the volume mount; outputs and samples land on the same volume so nothing is lost when the trainer instance is destroyed.