NVIDIA Tesla P40 · 24GB VRAM

TensorFlow GPU VPS

Ubrzajte radne opterećenja TensorFlow-a sa namjenskim NVIDIA GPU hardverom. Trenirajte modele, služite predviđanja i gradite ML kanale sa punom CUDA podrškom.

$ pip install tensorflow[and-cuda]
# Pokreće se na NVIDIA Tesla P40 (24GB)
Spreman. _

Šta je {ime} na GPU VPS-u?

TensorFlow je Google-ov okvir za mašinski učenje otvorenog koda za izgradnju i implementaciju modela ML. Sa GPU VPS, dobivate posvećen hardver za ubrzavanje obuke i zaključivanja bez dijeljenja resursa.

Zašto TensorFlow na VPS.org GPU

GPU ubrzanje

Nativna CUDA podrška za TensorFlow operacije. Do 50x brže od CPU.

Hardver kompatibilan

Potpuna Keras integracija za izgradnju modela visokog nivoa sa GPU backend.

TensorBoard

Nadziraj trening sa TensorBoard-om na svom serveru.

Spreman za posluživanje

Upotreba modela u proizvodnji sa TensorFlow Serving na GPU.

Popularni TensorFlow slučajevi upotrebe

Klasifikacija slika
Detekcija objekta
Prirodni jezik
Preporuka sistema
Time series forecasting
Produkcija ML cjevovoda

Specifikacije GPU-a

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
CUDA boje3,840
FP3212 TFLOPS
INT847 TOPS
Memorija346 GB/s
ArhitekturaPascal (GP102)
ProlazBare metal PCIe

Često postavljana pitanja

What is TensorFlow on a GPU VPS?

+

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?

+

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?

+

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?

+

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?

+

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?

+

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?

+

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?

+

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?

+

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?

+

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?

+

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?

+

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

Spreman za pokretanje TensorFlow na GPU?

Ugradite namjenski NVIDIA GPU server za nekoliko minuta. Bez rezervacija, bez prodajnih poziva.

Pokreni svoj VPS
Od $2.0/mjesečno