NVIDIA Tesla P40 · 24GB VRAM

TensorFlow GPU VPS

Accelerera TensorFlow arbetsbelastning med dedikerad NVIDIA GPU-maskinvara. Tågmodeller, tjäna förutsägelser, och bygga ML rörledningar med fullt stöd för CUDA.

$ pip install tensorflow[and-cuda]
# Körs på NVIDIA Tesla P40 (24GB)
Färdiga. _

Vad är {namn} på en GPU VPS?

TensorFlow är Googles ramverk för maskininlärning med öppen källkod för att bygga och distribuera ML-modeller. Med GPU VPS får du dedikerad hårdvara för att påskynda utbildning och slutsatser utan att dela resurser.

Varför {namn} på VPS.org GPU

GPU påskyndas

Native CUDA stöd för TensorFlow operationer. Upp till 50x snabbare än CPU.

Keras kompatibel

Fullständig Keras integration för högnivåmodellbyggnad med GPU-backend.

TensorBoard Ordförande

Övervaka träningen med TensorBoard på din egen server.

TF-servering klar

Utplacera modeller till produktion med TensorFlow Serving på GPU.

Populärt {namn} Användningsfall

Bildklassificering
Objektdetektering
Behandling av naturligt språk
Rekommendationssystem
Tidsserieprognoser
Produktion ML rörledningar

GPU-specifikationer

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
CUDA- kärnor3,840
FP3212 TFLOPS
INT8 Ordförande47 TOPS
Minne BW346 GB/s
ArkitekturPascal (GP102)
GenomströmningBare metal PCIe

Vanliga frågor

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.

Redo att köra {namn} på GPU?

Skicka en dedikerad NVIDIA GPU-server på några minuter. Inga reservationer, inga säljsamtal.

Starta din VPS
Från $2,0/mo