NVIDIA Tesla P40 · 24GB VRAM

TensorFlow GPU VPS

Versnel TensorVolg workloads met dedicated NVIDIA GPU hardware. Trein modellen, serveer voorspellingen, en bouw ML pijpleidingen met volledige CUDA ondersteuning.

$ pip install tensorflow[and-cuda]
# Draaien op NVIDIA Tesla P40 (24GB)
Klaar. _

Wat is {naam} op een GPU VPS?

TensorFlow is Google's open-source machine learning framework voor het bouwen en implementeren van ML-modellen. Met GPU VPS, krijg je speciale hardware om training en gevolgtrekkingen te versnellen zonder middelen te delen.

Waarom {naam} op VPS.org GPU

GPU versneld

Native CUDA ondersteuning voor TensorFlow operaties. Tot 50x sneller dan CPU.

Kera's compatibel

Volledige Keras integratie voor high-level modelbouw met GPU backend.

TensorBoard

Monitor training met TensorBoard op uw eigen server.

TF-server gereed

Stel modellen in om te produceren met TensorFlow Serving op GPU.

Popular TensorFlow Cases gebruiken

Afbeeldingsclassificatie
Objectdetectie
Natuurlijke taalverwerking
Aanbevelingssystemen
Voorspelling van tijdreeksen
Productie ML pijpleidingen

GPU Specificaties

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
CUDA-kernen3,840
KP3212 TFLOPS
INT847 TOPS
Geheugen BW346 GB/s
ArchitectuurPascal (GP102)
DoorvoerenBare-metal PCIe

Veelgestelde vragen

What is TensorFlow on a GPU VPS?

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TensorFlow on a GPU VPS is a CUDA-accelerated deployment. TensorFlow is a training / fine-tuning workload. Plan for long-running jobs — snapshot your VPS regularly, and consider an external cold-storage backup for trained weights.

How do I set up TensorFlow on a GPU VPS?

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Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install tensorflow[and-cuda]. Your TensorFlow environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for TensorFlow?

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Training VRAM is dominated by the optimizer state plus activations. Full fine-tuning of a 7B LLM needs ~24-48 GB; LoRA / QLoRA fits in 8-16 GB. Our Tesla P40 supports LoRA-class fine-tuning out of the box; full training of larger models requires multi-GPU.

Is TensorFlow 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 TensorFlow?

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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 TensorFlow.

Do I get full root on the TensorFlow GPU VPS?

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

Which CUDA version is installed for TensorFlow?

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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 TensorFlow workload.

Does my TensorFlow GPU VPS persist between sessions?

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Yes — your TensorFlow 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 TensorFlow workload?

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

Can I scale my TensorFlow 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 TensorFlow 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 TensorFlow 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 TensorFlow on a GPU VPS risk-free.

Klaar om TensorFlow op GPU uit te voeren?

Stel een NVIDIA GPU server in in enkele minuten. Geen reserveringen, geen verkoopgesprekken.

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Van $2,0/mo