NVIDIA Tesla P40 · 24GB VRAM

vLLM GPU Server

Kushandisa vLLM pane yakasarudzika NVIDIA GPU hardware, unogona kushandira mamodheru emhando yepamusoro yechirungu neyakakwira-yekufambisa.

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

Chii chinonzi {zita} paGPU VPS?

vLLM ndeye high-throughput LLM inoshandira injini iyo inoshandisa PagedAttention yekuchengetedza kuchengetedza.Kushanda vLLM paGPU VPS inokupa iwe LLM API yakagadzirira kugadzira nemhando yepamusoro.

Nei {zita} pa VPS.org GPU

PagedAttention

Efficient GPU memory management for higher throughput.

Kuenderera mberi Batching

Kudzora akawanda zvakaenzana zvinoda neakakodzera GPU kushandiswa.

OpenAI API

Drop-mu kuchinja OpenAI API endpoints.

Model Kutsigira

LLaMA, Mistral, Gemma, Qwen, uye 50 + mamodheru emabhizimusi.

Popular vLLM Usage Cases

Production LLM APIs
Chatbots ane huwandu hwakawanda hwekufambisa
Batch kuongorora
Multi-tenant LLM inoshandira
AI SaaS backends
Enterprise AI mapuratifomu

GPU Kuratidzwa

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
CUDA Cores3,840
FP3212 TFLOPS
INT847 TOPS
Kuchengeta346 GB/s
ArchitecturePascal (GP102)
KupindaBare-metal PCIe

Zvimwe zvinobvunzwa kakawanda

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.

Uchigadzirira kushandisa vLLM paGPU?

Kuisa a dedicated NVIDIA GPU server mumasekondi. No kugara, hapana kushambadza kufona.

Kutanga yako VPS
Kutanga pa $2.0/mwedzi