GPU Cloud Infrastructure

Vultr GPU Cloud – High-Performance GPU Instances

Deploy NVIDIA A100 & H100 GPU servers in minutes. Built for AI training, LLM inference, and GPU-accelerated workloads worldwide.

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GPU Specifications

GPU ModelComputeVRAMBandwidth
NVIDIA A100 80GB312 TFLOPS FP1680 GB HBM2e2.0 TB/s
NVIDIA H100 80GBLatest Gen3,958 TFLOPS FP880 GB HBM33.35 TB/s

VRAM Requirements by Model Size

~14 GB
7B params
FP16
1× A100
~26 GB
13B params
FP16
1× A100
~140 GB
70B params
FP16
2× A100 or 1× H100 NVL
~35–45 GB
70B params
4-bit
1× A100 (quantized)

What You Can Build

🤖

LLM Hosting & Inference

Serve LLaMA 3, Mistral, Mixtral, and Falcon models via vLLM or TGI. A single A100 80GB handles 70B models at 4-bit precision.

🎨

Stable Diffusion & Image AI

Run SDXL, ControlNet, and LoRA pipelines at scale. Generate thousands of images per hour with GPU-optimized diffusion settings.

🧬

AI Model Training

Full PyTorch/TensorFlow training runs with NVLink multi-GPU parallelism. Reduce training time from days to hours.

🎬

AI Video Generation

Deploy Wan2.1, CogVideoX, and Sora-class video models. GPU-accelerated video rendering and generation pipelines.

🔬

Scientific Compute

Molecular dynamics, fluid simulations, climate modeling, and Monte Carlo using CUDA-accelerated libraries.

📦

Vector Database & RAG

GPU-accelerated Faiss, Milvus, and Qdrant indexing for RAG pipelines handling billions of embeddings.

Related Technical Guides

Related Infrastructure Pages

GPU Cloud FAQ

What GPU types does Vultr offer?

Vultr offers NVIDIA A100 80GB and H100 80GB instances for enterprise AI workloads, plus consumer RTX-class GPUs for development and testing. All instances are available in multiple global regions.

How quickly can I deploy a Vultr GPU server?

GPU servers can be provisioned and running within minutes after account creation. Simply select your GPU type, region, and operating system, then deploy.

Can I use Vultr GPUs for LLM inference?

Yes. Vultr GPU instances are well-suited for running LLM inference with frameworks like vLLM, TGI, and Ollama. A single A100 80GB can serve 70B models with 4-bit quantization.

Do Vultr GPU servers support multi-GPU configurations?

Yes, Vultr supports multi-GPU instances with NVLink connectivity for high-bandwidth GPU-to-GPU communication, ideal for distributed training and large model serving.

Ready to Deploy on Vultr GPU Cloud?

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