NVIDIA Tesla P40 · 24GB VRAM

Server s vLLM GPU

Poskytujte veľké jazykové modely s maximálnou priepustnosťou pomocou vLLM na vyhradenom hardvéri grafických procesorov NVIDIA.

$ pip install vllm && vllm serve meta-llama/Llama-3-8B-Instruct --host 0.0.0.0
# Beží na NVIDIA Tesla P40 (24GB)
Pripravený. _

Čo je vLLM na GPU VPS?

vLLM je vysoko výkonný LLM server, ktorý využíva PagedAttention pre efektívnu správu pamäte.Spustenie vLLM na GPU VPS vám poskytuje produkčné LLM API s optimálnym výkonom.

Prečo vLLM na VPS.org GPU

PagedAttention

Efektívna správa pamäte GPU pre vyššiu priepustnosť.

Kontinuálne dávkovanie

Spracovávajte viacero súbežných požiadaviek s optimálnym využitím GPU.

OpenAI API

Drop-in náhrada za OpenAI API koncové body.

Podpora modelu

LLaMA, Mistral, Gemma, Qwen a viac ako 50 modelových architektúr.

Populárne prípady použitia vLLM

Výrobné LLM API
Chatboty s vysokou návštevnosťou
Dávkové spracovanie textu
Multi-tenant LLM slúžiace
AI SaaS backendy
Podnikové platformy umelej inteligencie

Špecifikácie GPU

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
Jadrá CUDA3,840
FP3212 TFLOPS
INT847 TOPS
Pamäť BW346 GB/s
ArchitektúraPascal (GP102)
PriechodnosťBare-metal PCIe

Často kladené otázky

What is vLLM on a GPU VPS?

+

vLLM on a GPU VPS is a CUDA-accelerated deployment. vLLM is primarily an LLM-inference / chat workload. You will want fast random-access reads from disk to memory and enough VRAM for the model plus context window.

How do I set up vLLM on a GPU VPS?

+

Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install vllm && vllm serve meta-llama/Llama-3-8B-Instruct --host 0.0.0.0. Your vLLM environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for vLLM?

+

LLM inference VRAM scales with model parameters. A 7B model needs ~5-8 GB VRAM, 13B ~10-14 GB, 70B requires multi-GPU or quantization. Our 24 GB Tesla P40 comfortably runs 7B-13B models at full precision and 30B-class models with INT8 quantization.

Is vLLM 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 vLLM?

+

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

Do I get full root on the vLLM GPU VPS?

+

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

Which CUDA version is installed for vLLM?

+

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 vLLM workload.

Does my vLLM GPU VPS persist between sessions?

+

Yes — your vLLM 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 vLLM workload?

+

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

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

Ste pripravení spustiť vLLM na GPU?

Nasaďte si vyhradený server s grafickými procesormi NVIDIA v priebehu niekoľkých minút. Žiadne rezervácie, žiadne predajné hovory.

Spustite svoj VPS
Od 2,0 USD/mesiac