NVIDIA Tesla P40 · 24GB VRAM

vLLM GPU सर्भर

समर्पित एनभिडिया जीपीयू हार्डवेयरमा vLLM प्रयोग गरेर अधिकतम थ्रोपुटको साथ ठूलो भाषा मोडेलहरू सेवा गर्नुहोस्। बक्स बाहिर OpenAI-सुसंगत एपीआई।

$ pip install vllm && vllm serve meta-llama/Llama-3-8B-Instruct --host 0.0.0.0
# एनभिडिया टेस्ला P40 (२४ जीबी) मा चलिरहेको
तयार । _

GPU VPS मा vLLM के हो?

vLLM एक उच्च-throughput LLM सेवा इन्जिन हो जुन कुशल स्मृति व्यवस्थापनको लागि PagedAttention प्रयोग गर्दछ। एक जीपीयू वीपीएसमा vLLM चलाउनुहोस् तपाईंलाई उत्तम प्रदर्शनको साथ उत्पादन-सज्जित LLM API दिन्छ।

Why vLLM on VPS.org GPU

पृष्ठ ध्यानाकर्षण

यसले उच्च गुणस्तरको ग्राफिक्स प्रदान गर्दछ ।

निरन्तर ब्याचिङ

उत्तम GPU उपयोगिता संग बहुविध एकैसाथ अनुरोध ह्यान्डल गर्नुहोस् ।

खुला AI एपीआई

यो पत्रिकाको प्रकाशक एपीएफ हो।

नमूना समर्थन

यसको मुख्यालय सिड्नी, क्यानडामा छ र यसमा ५०० भन्दा बढी कर्मचारीहरू छन्।

लोकप्रिय vLLM प्रयोग गर्नुहोस्

उत्पादन LLM एपीआईहरू
उच्च-ट्राफिक च्याटबोटहरू
ब्याच पाठ प्रक्रिया
बहु-किर्ते LLM सेवा
AI SaaS ब्याकइन्डहरू
उद्यम AI प्लेटफर्महरू

GPU निर्दिष्टता

जीपीयूNVIDIA Tesla P40
भिआरएम24 GB GDDR5X
CUDA रङ3,840
FP3212 TFLOPS
INT847 TOPS
स्मृति श्यामश्वेत346 GB/s
वास्तुकलाPascal (GP102)
पासथ्रूबेयर- मेटल PCIe

प्राय सोधिने प्रश्नहरू

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.

GPU मा vLLM चलाउन तयार हुनुहुन्छ?

मिनेटमा समर्पित एनभीडिया जीपीयू सर्भर तैनात गर्नुहोस्। कुनै रिजरभेसन, कुनै बिक्री कलहरू छैन।

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