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Image generation workflows

Rent a cloud GPU for Stable Diffusion and ComfyUI.

Direct answer

Stable Diffusion and ComfyUI workloads are usually best matched by the exact graph, checkpoint, resolution, batch and auxiliary models. RTX 4090 offers a $0.34/hour GPURento reference with 24 GB; RTX 5090 provides 32 GB at $0.69/hour; L40S offers 48 GB at $0.79/hour when a workflow needs more headroom.

Reviewed by the GPURento infrastructure team · September 1, 2026

Transparent planning windows

Example rental cost on one RTX 4090.

These are compute rental windows, not predictions of job duration or performance. Replace the hours with a measured pilot and add storage in the calculator.

Adjust every assumption

One work session

$2.72

1 GPU × 8h · compute only

Forty-hour window

$13.60

1 GPU × 40h · compute only

One-hundred-twenty hours

$40.80

1 GPU × 120h · compute only

Key facts for Rent a cloud GPU for Stable Diffusion and ComfyUI.
Value optionRTX 4090 · 24 GB$0.34/hour reference.
More headroomRTX 5090 · 32 GB$0.69/hour reference.
Large graphsL40S · 48 GB$0.79/hour reference.
Compare by$ / accepted outputKeep resolution, steps and model fixed.
Best for
  • ComfyUI node graphs
  • Stable Diffusion and FLUX-style image workflows
  • LoRA testing and batch generation
  • Persistent model libraries with repeat usage
Not the best fit when
  • Graphs with unknown custom-node provenance
  • Workflows that exceed the selected VRAM
  • Sensitive inputs without a reviewed storage and retention plan

Decision method

What to verify before you deploy capacity.

The content below separates published specifications, GPURento catalog references and decisions that still require a workload benchmark.

01

Package the workflow so it can be repeated

Pin the container, ComfyUI version, custom-node commits, checkpoint hashes and input settings. A visual graph without versioned dependencies is not a reproducible workload.

02

Size for peak graph memory

The checkpoint is only one memory consumer. VAEs, ControlNet, upscalers, text encoders and video nodes can overlap. Run a representative high-resolution job and record peak allocation before choosing the cheapest card.

  • Start with the largest expected resolution
  • Test the full auxiliary-model graph
  • Keep output and model storage separate from compute
03

Compare cost per accepted image or clip

Record warm run time, rejected outputs and total metered GPU time. Model download and node installation make cold runs slower, which is why persistent storage may be valuable for repeat sessions.

Catalog shortlist

Relevant GPU options.

Open GPU selector
AdaAvailable

NVIDIA RTX 4090

24 GB GDDR6X · $0.34/hr

Image, video and mid-size inference

EU West · ParisEU Central · Frankfurt
BlackwellAvailable

NVIDIA RTX 5090

32 GB GDDR7 · $0.69/hr

Fast single-GPU inference and media

EU West · ParisEU Central · Frankfurt
AdaAvailable

NVIDIA L40S

48 GB GDDR6 ECC · $0.79/hr

Production inference, fine-tuning and video

EU West · ParisEU Central · Frankfurt

Questions

Clear answers, including the limits.

What GPU should I rent for ComfyUI?+

RTX 4090 is a strong starting point for graphs that fit 24 GB. Choose RTX 5090 for 32 GB or L40S for 48 GB when the actual workflow requires more memory.

Does GPURento provide a one-click ComfyUI template?+

This page does not claim a one-click template. The GPU Cloud accepts container configuration; confirm the image and workflow requirements in the workspace.

How do I keep costs down?+

Persist reusable models, stop compute after outputs are saved, and compare cost per accepted output rather than peak images per second.

Deployment plan

Request the GPU that fits the full graph.

Create a workspace with the exact image, storage and region settings, then fund it before requesting capacity.

Create workspace Review pricing