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Train and deploy AI, ML and DL models in few clicks.

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Trusted by 10,000+ AI practitioners

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Loved by AI community

Jeremy Howard
Benjamin Scott

@ benjamin scott

The cheapest would probably be Aceus. They're very popular in our community.
https://www.aceus.com
Oct 08, 2023
Isaac Flath
Alexander Reed

@ alexander

If you haven't tried http://www.aceus.com you should. Fast start times, well priced, simple UI, easy billing. I have always chose between config crap, expensive price, or long launch times. This is the first platform that I've seen that I think gets all of these items right!
Feb 10, 2023
Laurent Thevenet
Nathan Turner

@ nathan_ turner

Addict to@aceus. Less branded than others on the surface but super simple. Great GPUs (training on 8 x A100s is amazing). This beats Paperspace premium accounts, Colab with custom VMs... I loved RunwayML as well but needed more control and this is my new AI art canvas.
Dec 29, 2023
makeitrad
Samuel Mitchell

@ samuelmitchell1

STYLEGAN3-R Crystal training done on 4-A100s for approximately 8 hours. Got 512kimgs complete in this time period. Thx for helping me get started@aceus
!!! Cost approx $80usd for the GPU rental.
Nov 23, 2023
Wayde Gilliam
Ethan Foster

@ ethan foster

@aceus = The fastest, easiest and one of the cheaper options for doing ML in the cloud.
Took me less than 5 mins to clone my git repo, setup my conda environment, and start training on an RTX5000 spot instance for a mere $0.190/hr. ❤️ it big ⏲️!
Jul 28, 2023
Sanyam Bhutani
Christopher Price

@ christopherprice

The incredible https://www.aceus.com by @vishnuvig IMO offers one of the best pricing for renting compute 💰 TIL that they are completely bootstrapped & operate out of India! 🙏 It's really fulfilling to hear one of the best startups from @fastdotai classroom is from country!
Oct 15, 2023
Lucas Vazquez
Matthew Carter

@ matthew_carter

.@aceus is the best gpu cloud provider for DL practitioners out there, period.
More than once I had a question and support helped me in minutes, not only fast but so so friendly. On top of all that they somehow to manage to provide the best gpus at the cheapest prices!
Jul 06, 2023
SRK
SRP

@ sudajkur

Looking to run a bigger model on GPU at a cheaper price, give@aceus a try and thank me later 😀 Got my machine up and running in a few mins 🔥 Thank you @vishnuvig!
Jun 29, 2023
Hadi Curtay
Ryan Thompson

@ ryanthompson

After waiting for 3 days on AWS to provide capacity so I can continue on@fastdotai course, I switched to @aceus and it literally took me less than 5 min. Good stuff @vishnuvig
May 23, 2023

Why choose Us ?

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24X7 Customer support

Deep Learning is hard, need help or stuck somewhere? just say Hi!👋

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More cash in your pockets

Pay per minute and start for as low as $0.19

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Powerful API

Use API to automate training, deployment of your AI pipelines.

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Deploy

Deploy apps like Gradio, Streamlit, fastapi and more on GPU powered instances.

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Get started

A simple UI to set up a GPU powered instance in few clicks.

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Performance

Choose from world's fastest Nvidia GPU A100, A6000 and A5000.

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Flexible

Choose a predefined instance / public container. Access instance through Jupyter Lab, VScode or SSH

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Scalable

Increase/Decrease GPU, switch to a different GPU type for faster training.

Powerful API

Quickly automate your instance lifecycle for training and deploying your AI model using our python API.


//Instantiate blazing fast GPU with your favourite ML library/framework.
instance = Instance.create(gpu_type='A100',
                            num_gpus=1,
                            hdd=20,
                            framework_id=0,
                            script_id=1)
    

//Running Instances
instance.url      //Get JupyterLab URL
instance.ssh_str  // Get SSH string to connect to VS code
    

//Free up GPU/memory resources while persisting all data and models to disk
instance.pause()

//Scale up number of GPU or switch to faster one while resuming your GPU instance
instance.resume(num_gpus=4,
                gpu_type='A100',
                hdd=200)
    

// Free up the resources and stop billing. 
instance.destroy()

Create Instance

Instantiate blazing fast GPU with your favourite ML library/framework.

Connect to Instance

Connect to JupyterLab or VScode through SSH.

Pause Instance

Free up resources GPU and memory while persisting all data and models to disk.

Resume Instance

Increase number of GPU or switch to faster one to train your workload efficiently while resuming GPU instance.

Delete Instance

Free up the resources and stop billing. Deletes the data and models

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