Stable Diffusion Cloud Hosting India 2026 — From $0.21/hr
Run SD, SDXL, SD3, Flux image gen with ComfyUI / AUTOMATIC1111
Why AIC Cloud GPU for Stable Diffusion?
- ✓RTX 4090 at $0.21/hour — perfect for Stable Diffusion (24 GB VRAM)
- ✓A100 80GB for batch generation or SDXL with high resolution
- ✓INR billing via UPI for Indian image gen users
- ✓Pre-installed CUDA + PyTorch + xformers
- ✓Run ComfyUI, AUTOMATIC1111 WebUI, Forge, InvokeAI
Quick Start — Stable Diffusion on AIC Cloud GPU
- 1Provision AIC Cloud RTX 4090 instance at /cloud-gpu ($0.21/hr)
- 2Install AUTOMATIC1111: `git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui`
- 3Run setup: `cd stable-diffusion-webui && ./webui.sh --listen --enable-insecure-extension-access`
- 4Download models to /models/Stable-diffusion (SDXL Base + Refiner from Hugging Face)
- 5Access WebUI via VPS public IP on port 7860 (with auth)
Features
Frequently Asked Questions — Stable Diffusion
Which GPU is best for Stable Diffusion?
RTX 4090 ($0.21/hr) is the best value — 24 GB VRAM fits SDXL with all extensions (ControlNet, LoRA stacks, etc.). A100 80GB ($0.31/hr) is excellent for batch generation or training. For commercial production at scale, H100 ($1.99/hr) provides highest throughput.
Should I use ComfyUI or AUTOMATIC1111?
AUTOMATIC1111: easier to start, popular extension ecosystem, classic UI. ComfyUI: node-based workflow, more flexible, better performance for complex pipelines. Forge: AUTOMATIC1111 fork with better performance. For artists, A1111. For developers building image gen pipelines, ComfyUI.
Can I train custom LoRAs on AIC Cloud?
Yes — LoRA training of SDXL fits on RTX 4090 (24 GB VRAM) for small datasets (20-100 images). For larger datasets or higher batch sizes, use A100 80GB. Use kohya_ss or sd-scripts for LoRA training workflow.
How fast can I generate images?
RTX 4090 with SDXL: ~3-5 seconds per 1024x1024 image (20 steps). With batch of 4: ~10-15 seconds total (~3-4 sec/image effective). A100 80GB is ~30% faster for batch generation. For production image API, vLLM-style batching dramatically improves throughput.
Can I host an image generation API?
Yes — wrap your model with FastAPI/Flask, expose via Nginx, deploy on AIC Cloud GPU instance. For higher throughput, use ComfyUI as backend with custom API wrapper. Cold-start latency is ~30-60 seconds (model load), so keep instance running for production.
Related
Ready to deploy Stable Diffusion on AIC Cloud GPU?
RTX 4090 from $0.21/hr (~₹19/hr) · Hourly billing · INR via UPI
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