1. Choose a graphics card model
ML/AI GPUs by NVIDIA
We compare tensor core performance because these cards' primary use case is ML.
V100 SXM 16GB VRAM
125 TFLOPS TF32: Industry standard AI GPU, available NVLink'd together.
General Purpose GPUs by NVIDIA
We compare FP32 performance because these cards can be used for any use case.
2. Select how many GPUs
3. Customize RAM amount
4. Customize vCPU count
5. Customize storage
6. Select a location
Not all locations will be available for a selected machine configuration. Learn more about our data centers.
Chicago DC1, USA Best Overall Stock
Our largest location with the broadest set of GPUs available. Less than 50ms to all major U.S. cities.
Las Vegas DC1, USA Best VFX GPU Availability
Dozens of racks of A40s and other VFX-optimized GPUs. 10ms to Los Angeles, 35ms to Seattle.
7. Select an operating system
Operating system templates updated on July 28, 2022. Check out our Windows 10 Parsec cloud gaming article if this will apply for you.
TensorML 20 TensorFlow ML / AI
Jupyter, TensorFlow, Keras, CUDA, 25GB
Requires 40GB+ disk
TensorML 20 Everything ML / AI
Jupyter, TensorFlow, PyTorch, Keras, MxNet, fastai, CUDA, 40GB
Requires 60GB+ disk
8. Configure details
Your actual charge will be pro-rated to the
1x Undefined GPU
4 GB RAM
20 GB NVMe SSD
Chicago DC1, USA
TensorML 20.04 LTS
Learn more here.
We don't know the exact stock at the moment, but your selected machine configuration should be available. If your server isn't provisioned within 10 minutes, delete it and contact support.
Cost per hour when the VM is running.
Cost per hour when the VM is stopped.
Email us at firstname.lastname@example.org if you
spending over $10k/month and are interested in
a long term contract. Save 25% with a 12 month
commit and 40% with a 24 month commit.
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