NVIDIA Tesla P40 · 24GB VRAM

Machine Learning GPU VPS

Accelerate machine learning with GPU-powered training and inference. RAPIDS, XGBoost GPU, and scikit-learn on dedicated NVIDIA hardware.

$ pip install cuml-cu12 xgboost cudf-cu12
# Running on NVIDIA Tesla P40 (24GB)
Ready. _

What is Machine Learning on a GPU VPS?

GPU-accelerated machine learning uses NVIDIA CUDA to speed up training and predictions for classical ML algorithms. RAPIDS and XGBoost GPU can deliver 10-100x speedups over CPU-only implementations.

Why Machine Learning on VPS.org GPU

RAPIDS cuML

GPU-accelerated scikit-learn compatible algorithms.

XGBoost GPU

Train gradient boosting models 10x faster on GPU.

cuDF & cuPy

GPU-accelerated pandas and numpy for data preprocessing.

End-to-End GPU

Keep your entire ML pipeline on GPU for maximum speed.

Popular Machine Learning Use Cases

Classification & regression
Feature engineering at scale
Real-time predictions
Large dataset processing
AutoML pipelines
Model benchmarking

GPU Specifications

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
CUDA Cores3,840
FP3212 TFLOPS
INT847 TOPS
Memory BW346 GB/s
ArchitecturePascal (GP102)
PassthroughBare-metal PCIe

Frequently Asked Questions

What is Machine Learning on a GPU VPS?

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Machine Learning on a GPU VPS is a CUDA-accelerated deployment. Machine Learning is a general GPU-accelerated workload. Make sure your software has CUDA support and that your driver / runtime versions match the workload requirements for Machine Learning.

How do I set up Machine Learning on a GPU VPS?

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Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install cuml-cu12 xgboost cudf-cu12. Your Machine Learning environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for Machine Learning?

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Our GPU VPS ships with 24 GB GDDR5X VRAM on the NVIDIA Tesla P40, which is sufficient for most Machine Learning workloads. Multi-GPU configurations are available on request.

Is Machine Learning GPU VPS billed hourly or monthly?

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GPU VPS plans are billed monthly with no lock-in contracts and can be cancelled anytime. Contact us for current GPU pricing tiers.

Can I run other tools alongside Machine Learning?

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Yes — you have full root on the GPU VPS. Run whatever fits inside the 24 GB VRAM and the available RAM / storage budget alongside Machine Learning.

Do I get full root on the Machine Learning GPU VPS?

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Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for Machine Learning however you need.

Which CUDA version is installed for Machine Learning?

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GPU VPSs ship with a recent CUDA runtime and the matching NVIDIA driver pre-installed. You can pin or upgrade CUDA versions as required by your Machine Learning workload.

Does my Machine Learning GPU VPS persist between sessions?

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Yes — your Machine Learning GPU VPS is a long-running persistent server, not an ephemeral instance. Models, configs, and data stay on the SSD between sessions.

Where should I store data for my Machine Learning workload?

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Keep working data on the VPS SSD for fast access during Machine Learning runs; back up finished artifacts (weights, generations, embeddings) off-server via snapshots or object storage for safety.

Can I scale my Machine Learning GPU VPS later?

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Yes — plan upgrades are instant from your control panel; the GPU itself can be swapped to a larger tier on request. Your Machine Learning install carries over.

Are backups available for my GPU VPS?

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Yes. Automated daily backups are an add-on; manual snapshots are free. Useful for long Machine Learning training runs where you want a checkpointable server state.

Is there a money-back guarantee on the GPU VPS?

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Yes — 30-day money-back guarantee on every plan including GPU. Try Machine Learning on a GPU VPS risk-free.

Ready to Run Machine Learning on GPU?

Deploy a dedicated NVIDIA GPU server in minutes. No reservations, no sales calls.

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From $2.0/mo