L40 on Vultr
Visit VultrVultr's NVIDIA L40 GPU offering delivers enterprise-grade compute for AI inference, visualization, and rendering workloads, powered by the Ada Lovelace architecture with 48GB GDDR6 VRAM. This combination leverages Vultr's expansive global footprint across 32+ regions, enabling low-latency deployments for distributed ML applications. Ideal for ML engineers and data scientists handling large models like LLMs or generative AI, the L40 provides exceptional inference throughput—up to 1,500+ TOPS in INT8—while balancing compute density and efficiency. Key value propositions include flexible hourly billing for cost-effective scaling, seamless integration with Vultr's ecosystem (object storage, managed Kubernetes, block storage), and rapid provisioning without long-term commitments. This setup excels in production inference serving, VDI, and Omniverse workflows, offering a compelling alternative to hyperscalers with superior regional coverage and no egress fees on internal traffic. Limitations include potential variability in multi-GPU interconnects compared to on-prem setups.
Why NVIDIA L40 on Vultr?
Choose Vultr for NVIDIA L40 when global reach and flexibility are paramount. Vultr's 32+ regions minimize inference latency for worldwide users, outperforming providers with sparser footprints. The L40's inference optimizations (TensorRT, Transformer Engine) complement Vultr's high-bandwidth networking (up to 25Gbps) and NVMe storage, accelerating data-intensive ML pipelines. Hourly billing suits bursty workloads, prototyping, or seasonal scaling without upfront costs. Integrated services like load balancers and VPCs simplify multi-GPU clusters and orchestration. This combo avoids vendor lock-in, supports rapid iteration, and delivers cost savings via efficient resource utilization—ideal for teams prioritizing geographic diversity over raw hyperscale density.
Live Pricing
Real-time NVIDIA L40 offers from Vultr
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | 2×NVIDIA L40S 48GB VRAM | 48GB | 32 vCPU 375GB RAM 2200GB Storage | Atlanta | $1.67/GPU/hr $3.34/hr total (2×) | Sold Out | ||
Vultr | 2×NVIDIA L40S 48GB VRAM | 48GB | 32 vCPU 375GB RAM 2200GB Storage | Atlanta | $1.67/GPU/hr $3.34/hr total (2×) | Sold Out | ||
Vultr | 4×NVIDIA L40S 48GB VRAM | 48GB | 64 vCPU 750GB RAM 2600GB Storage | 🌍global | $1.67/GPU/hr $6.68/hr total (4×) | Sold Out | ||
Vultr | NVIDIA L40S 48GB VRAM | 48GB | 16 vCPU 180GB RAM 1200GB Storage | Atlanta | $1.67/GPU/hr | Sold Out | ||
Vultr | 8×NVIDIA L40S 48GB VRAM | 48GB | 128 vCPU 1500GB RAM 3400GB Storage | 🌍global | $1.67/GPU/hr $13.37/hr total (8×) | Sold Out |
Performance Notes
Vultr's L40 delivers robust performance: ~90 TFLOPS FP32, 362 TFLOPS FP16, and 1,509 TOPS INT8 for inference-heavy tasks. Expect 10-50Gbps networking bandwidth for inter-instance communication, supporting distributed training via Ethernet (NVLink unconfirmed). Pair with high-IOPS NVMe block storage (up to 14K IOPS) for fast dataset access. Multi-GPU scaling works via clustering, though efficiency depends on workload—strong for inference, moderate for training vs. H100. Benchmarks indicate L40 rivals A100/H100 in Omniverse/rendering at lower power (300W). Actual results vary by software stack (CUDA 12+); user testing recommended as provider-specific optimizations are limited.
A global cloud provider with a massive footprint for deployments across numerous regions.
Best For
Unique Features
- Massive global footprint
- Integrated cloud services
VRAM
48GB
Architecture
Ada Lovelace
Tier
enterprise
Platform Features
Getting Started
Getting started with NVIDIA L40 on Vultr is quick via the intuitive cloud console. Select from 32+ regions, deploy CUDA-preloaded images, and access GPU-accelerated environments in minutes. Suited for ML prototyping to production inference, with hourly billing for easy experimentation.
Steps
- 1Create a Vultr account, verify email, and add a payment method.
- 2Go to Products > Cloud Compute > GPU, select NVIDIA L40 instance type.
- 3Choose region, plan size, OS image (e.g., Ubuntu 22.04 + CUDA), and deploy.
- 4Once running, SSH into the instance using provided credentials.
- 5Verify GPU with 'nvidia-smi', install frameworks like PyTorch via pip.
Pro Tips
- Use Vultr Marketplace one-click apps for pre-configured CUDA, Docker, and ML frameworks to skip manual setup.
- Attach high-performance block storage early and enable auto-scaling for cost-efficient multi-GPU workloads.
- Monitor resource usage in the Vultr dashboard; leverage reserved IPs for persistent global access.
Frequently Asked Questions
What is Vultr's billing model for NVIDIA L40?▾
Vultr bills per-hour for GPU instances including NVIDIA L40. 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 L40?▾
No, Vultr does not currently offer spot instances for NVIDIA L40. 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 L40?▾
Yes, Vultr offers reserved instance pricing for NVIDIA L40, 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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