NVIDIA Tesla P40 · 24GB VRAM

GPU Cliser

Tumieni violezo vikubwa vya lugha ambavyo vimejikita sana kwa kutumia alama ya vLLM kwenye chombo cha GPIA.

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

Jina la Kiingereza la NGOGS ni nini katika shirika la GPU VPS?

LLLM ni injini inayotumika kama Ukurasa wa makini kwa ajili ya usimamizi mzuri wa kumbukumbu. Bock vLLLM kwenye GPU VPPS inakupa nafasi ya kutengeneza LLM API kwa matokeo bora kabisa.

Kwa nini jina la Ntowachi mnamo VPS.org GPU

Ukurasa wa Kukazia Fikira

Uhifadhi wa kumbukumbu wa GPU kwa ajili ya habari za hali ya juu.

Kokwa Yenye Kuendelea

Fanya maombi mengi ya wakati ujao kwa kutumia GPU.

OpenAI API

Kuanguka na kuchukua mahali pa alama za wazi za fursaI API.

Utegemezo wa Mfano

LLaMA, Mistaril, Gemma, Qwen, na majengo 50+ ya mitindo.

Jina lipendwalo na wengi la Kanali Utumia Visa

CHEMBE ZA Utokezwaji
Vituo vya maongezi vya hali ya juu
Ushughulikiaji wa maandishi - awali
paper size
MAHUSIANO YA AI SaaS
Bafu za AI zilizojipinda - pinda

Muundo wa GPI

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
CUDA Cores3,840
FP3212 TFLOPS
INTI847 TOPS
Kumbukumbu BW346 GB/s
UjenziPascal (GP102)
Kupitia" Bare-metal PCIe "

Maswali Ambayo Watu Huuliza Mara Nyingi

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.

Je, uko tayari Kutangaza jina la NJEli kwenye GPU?

Deptoy a IVIDIA GPU server kwa dakika chache.

Omboleza UPS wako
Kutoka dola 2.0/mo