A100 PCIe 80GB on Vultr
Visit VultrVultr's NVIDIA A100 PCIe 80GB offering delivers enterprise-grade AI acceleration through NVIDIA's Ampere architecture GPU with 80GB HBM2e VRAM, optimized for memory-intensive workloads like large language model training, inference, and HPC simulations. With Vultr's expansive global footprint across 32+ regions, users achieve low-latency deployments worldwide, ideal for ML engineers and data scientists handling distributed AI pipelines. Key value propositions include flexible per-hour billing for cost-efficient scaling, high-performance NVMe storage, and integrated services such as Kubernetes Engine and managed databases. This combination stands out for its reliability in production environments, supporting multi-GPU configurations up to 4x or more in dedicated plans. Whether bursting for training jobs or serving models globally, Vultr ensures seamless integration with standard ML frameworks like PyTorch and TensorFlow, backed by straightforward provisioning and robust networking up to 10Gbps sustained.
Why NVIDIA A100 PCIe 80GB on Vultr?
Vultr pairs the A100 PCIe 80GB's massive 80GB VRAM—perfect for handling billion-parameter models—with its unmatched 32+ region footprint, enabling global edge deployments with minimal latency. Hourly billing provides pay-as-you-go flexibility, ideal for intermittent ML workloads without lock-in. Strengths include high-speed NVMe SSDs for fast data I/O, 10Gbps networking for efficient data transfers, and easy scaling to multi-GPU setups via standard PCIe interconnects. Integrated tools like Vultr Cloud GPU, Marketplace apps for CUDA/Docker, and Kubernetes simplify orchestration. This combo excels over regional providers by combining A100's computational density with worldwide availability, making it a top choice for international teams prioritizing reach and economics.
Live Pricing
Real-time NVIDIA A100 PCIe 80GB offers from Vultr
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | 2×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 12 vCPU 120GB RAM 1400GB Storage | New Jersey | $1.20/GPU/hr $2.40/hr total (2×) | Sold Out | ||
Vultr | 2×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 12 vCPU 120GB RAM 1400GB Storage | 🌍global | $1.20/GPU/hr $2.40/hr total (2×) | Sold Out | ||
Vultr | 2×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 12 vCPU 120GB RAM 1400GB Storage | Silicon Valley | $1.20/GPU/hr $2.40/hr total (2×) | Sold Out | ||
Vultr | 2×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 12 vCPU 120GB RAM 1400GB Storage | Tokyo | $1.20/GPU/hr $2.40/hr total (2×) | Sold Out | ||
Vultr | 8×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 48 vCPU 480GB RAM 1400GB Storage | New Jersey | $1.20/GPU/hr $9.59/hr total (8×) | Sold Out |
Performance Notes
Vultr's A100 PCIe 80GB delivers expected Ampere performance: up to 19.5 TFLOPS FP32, 312 TFLOPS FP16 with sparsity, leveraging PCIe 4.0 for solid host communication. Instances feature NVMe storage (e.g., 1-4TB) for rapid dataset loading and 10Gbps networking (300Gbps bursts) suitable for distributed training. Multi-GPU scaling works via software frameworks like NCCL, though PCIe limits NVLink speeds—effective for 2-8 GPU configs. Real-world MLPerf results are competitive with on-prem; exact Vultr benchmarks are limited but align with provider disclosures. Unknowns include precise interconnect latency—recommend user benchmarking for custom workloads. Hourly access facilitates affordable testing.
A global cloud provider with a massive footprint for deployments across numerous regions.
Best For
Unique Features
- Massive global footprint
- Integrated cloud services
VRAM
80GB
Architecture
Ampere
Tier
enterprise
Platform Features
Getting Started
Launch Vultr's NVIDIA A100 PCIe 80GB via the user-friendly cloud console. Select from optimized GPU plans in 32+ regions, deploy CUDA-ready images, and scale with hourly billing. Ideal for quick ML prototyping to production, with built-in Marketplace apps for PyTorch, TensorFlow, and Jupyter.
Steps
- 1Sign up for Vultr account, verify email, and add billing method.
- 2Go to Products > Cloud GPU, select A100 PCIe 80GB plan and region.
- 3Choose OS/image (e.g., Ubuntu 22.04 + CUDA 12) and configure resources.
- 4Deploy instance; note public IP and SSH key setup.
- 5Connect via SSH, pull Docker images, and run your ML workload.
Pro Tips
- Use Vultr Marketplace one-click apps for pre-installed ML frameworks to accelerate setup.
- Attach high-performance Block Storage volumes for datasets and enable auto-snapshots.
- Monitor GPU utilization with nvidia-smi and Vultr metrics for optimal resource tuning.
Frequently Asked Questions
What is Vultr's billing model for NVIDIA A100 PCIe 80GB?▾
Vultr bills per-hour for GPU instances including NVIDIA A100 PCIe 80GB. Hourly billing means you pay for full hours even if your job completes mid-hour. Plan your workloads accordingly to maximize cost efficiency.
Does Vultr offer spot instances for NVIDIA A100 PCIe 80GB?▾
No, Vultr does not currently offer spot instances for NVIDIA A100 PCIe 80GB. All instances are billed at on-demand rates. However, they do offer reserved instances for committed usage, which can provide significant discounts for long-term workloads.
Does Vultr offer reserved instances for NVIDIA A100 PCIe 80GB?▾
Yes, Vultr offers reserved instance pricing for NVIDIA A100 PCIe 80GB, which can provide significant discounts (typically 20-40% off on-demand rates) for committed usage periods. Reserved instances are ideal for predictable, long-running workloads like production inference services, ongoing training pipelines, or development environments that run continuously. Contact Vultr for current reserved pricing and commitment terms.
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