NVIDIA Tesla P40 · 24GB VRAM

Mai Sarrafa GPU na vLLM

Yi amfani da manyan sifofin harshe tare da mafi girman gudu ta amfani da vLLM akan kayan aikin NVIDIA GPU. OpenAI-compatible API daga akwatin.

$ pip install vllm && vllm serve meta-llama/Llama-3-8B-Instruct --host 0.0.0.0
# Ana tafiyar da shi a kan NVIDIA Tesla P40 (24GB)
A'aha! _

Mece ce {nama} a kan wani GPU VPS?

vLLM wani mai sarrafa LLM mai tsada ne wanda ke amfani da PagedAttention don kula da ƙwaƙwalwar ƙwaƙwalwa. Running vLLM akan GPU VPS yana ba ka API mai shirya LLM tare da kyakkyawan aiki.

Me yasa {nama} akan VPS.org GPU

PagedAttention

Manajan hankalin GPU mai inganci don tsawo.

QPrintPreviewDialog

Manajan tambayoyi masu yawa da suke gudana a lokaci guda tare da amfani da GPU mai kyau.

OpenAI API

Sauya-a-kashe ga maɓallan ƙarshe na OpenAI API.

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LLaMA, Mistral, Gemma, Qwen, da 50+ kayan aikin zane-zane na siffa.

{nama} Kasuwanci Masu Sauƙaƙe

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Chatbots masu yawan zirga-zirga
QDialogButtonBox
Multi-tenant LLM serving
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Pjatrformar AI na Kamfani

Bayanin GPU

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
@ action3,840
KCharselect unicode block name12 TFLOPS
KCharselect unicode block name47 TOPS
KWrite346 GB/s
KCharselect unicode block namePascal (GP102)
QShortcutBare-metal PCIe

Tambayoyi da ake yi da yawa

What is vLLM on a GPU VPS?

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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?

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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?

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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?

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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 vLLM?

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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 vLLM.

Do I get full root on the vLLM GPU VPS?

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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?

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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 vLLM workload.

Does my vLLM GPU VPS persist between sessions?

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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?

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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?

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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 vLLM 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 vLLM 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 vLLM on a GPU VPS risk-free.

An shirya don Run {nama} akan GPU?

Yi amfani da mai ba da sabis na NVIDIA GPU a cikin minti. Babu ajiya, babu kiran sayarwa.

QDialogButtonBox
Daga $2.0/mo