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OPEN MODELS / Image editing and upscaling

Run ChronoEdit-14B-Diffusers-Upscaler-Lora on a cloud GPU

ChronoEdit-14B-Diffusers-Upscaler-Lora is a Image editing and upscaling model by nvidia. See how much GPU memory it needs, which GPUs it fits on today and what it costs to run it yourself, billed per second.

Rent Q RTX 8000 from $0.48/hr
Parameters
≈ 14B
GPU memory needed
≈ 35 GB
License
apache-2.0
Downloads
239
Updated Nov 21, 2025

GPUs it fits on today

Our estimate is about 35 GB for inference with BF16 weights, including working memory. Real use depends on resolution, batch size and context length.

GPUMemoryPer hour10 hours
Q RTX 800045 GB$0.48$4.80Rent
CMP 170HX64 GB$0.62$6.20Rent
GB10119 GB$0.71$7.10Rent
A100 SXM480 GB$0.72$7.20Rent
RTX A600048 GB$0.72$7.20Rent

Live starting prices from our catalog. You pay per second while the machine runs.

How to run ChronoEdit-14B-Diffusers-Upscaler-Lora

  1. 01

    Rent a GPU

    Pick one of the GPUs above. Billing is per second; stop the machine and you stop paying.

  2. 02

    Open a terminal or Jupyter

    Connect over SSH or open Jupyter in your browser. PyTorch and CUDA are ready to use.

  3. 03

    Download and run the model

    Run the commands below. The weights download straight from Hugging Face to your machine.

pip install -U diffusers transformers accelerate
huggingface-cli download nvidia/ChronoEdit-14B-Diffusers-Upscaler-Lora --local-dir ./model
python -c "import torch; from diffusers import DiffusionPipeline; p = DiffusionPipeline.from_pretrained('./model', torch_dtype=torch.bfloat16).to('cuda'); print(p)"

Why run it yourself?

Batch editing and upscaling are heavy jobs. A cloud GPU finishes them quickly and you stop paying when the job is done.

Questions

How much GPU memory does ChronoEdit-14B-Diffusers-Upscaler-Lora need?
By our estimate about 35 GB for inference (14B parameters). Higher resolution, longer context or bigger batches need more.
How much does it cost to run ChronoEdit-14B-Diffusers-Upscaler-Lora?
From $0.48 per hour on Q RTX 8000, billed per second. Ten hours cost about $4.80.
Do I need a subscription?
No. You pay only for the time your machine runs, from your USD balance. Stop it whenever you are done.

Try it on your own GPU in minutes

Pick a GPU, open Jupyter or SSH and run any open model. You pay per second and can stop anytime; no subscription, no setup fee.

  • Per-second billing in USD
  • PyTorch and CUDA ready in minutes
  • Rent from ChatGPT or Claude too

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