Lambda Hyperplane-16
GPU Server with 16 Tesla V100s
Up to sixteen Tesla V100 GPUs with NVLink. Save up to 90% by moving your Deep Learning workload from cloud to on-premise.
Trusted by thousands of customers worldwide
Researchers and engineers at universities, start-ups, Fortune 500s, public agencies, and national labs use Lambda to power their artificial intelligence workloads.
Bestsellers
Our most popular options
Our bestsellers are designed to avoid CPU, memory, and storage bottlenecks for deep learning workloads.
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Basic
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16x Tesla V100 Server |
| 16-Way NVLink |
| 2x Xeon Platinum 8268 (24 Cores) |
| 768 GB of System Memory |
| 1.92 TB NVMe OS Drive |
| Customizable Data Drives |
| - |
| - |
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$
224,632
Academic Discounts
COVID-19 Research Discounts
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| Customize |
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Premium
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16x Tesla V100 Server |
| 16-Way NVLink |
| 2x Xeon Platinum 8268 (24 Cores) |
| 1.5 TB of System Memory |
| 1.92 TB NVMe OS Drive |
| Customizable Data Drives |
| Dual-Port 100 Gb/sec Ethernet/IB for Storage |
| 8x 100 Gb/sec IB for Multi-Node Training |
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$
241,392
Academic Discounts
COVID-19 Research Discounts
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| Customize |
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Max
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16x Tesla V100 Server |
| 16-Way NVLink |
| 2x Xeon Platinum 8280M (28 Cores) |
| 3 TB of System Memory |
| 1.92 TB NVMe OS Drive |
| Customizable Data Drives |
| Dual-Port 100 Gb/sec Ethernet/IB for Storage |
| 8x 100 Gb/sec IB for Multi-Node Training |
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$
271,920
Academic Discounts
COVID-19 Research Discounts
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| Customize |
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custom
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4x or 8x Tesla V100 |
| NVLink |
| Any Processor |
| Up to 768 GB RAM |
| Fully Customizable Storage |
| 100 Gbps InfiniBand |
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+1 (866) 711-2025
enterprise@lambdalabs.com
Academic Discounts
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| Live Chat |
Not seeing what you're looking for?
GPUs, processors, storage, networking, and memory are fully customizable. Get in touch and we'll design a system that matches your specifications.
Explore Lambda's Research
Our research papers have been accepted into the top machine learning and graphics conferences, including ICCV, SIGGRAPH Asia, NeurIPS, and ACM Transactions on Graphics (TOG).
HoloGAN: Unsupervised Learning of 3D
Representations from Natural Images
We propose a novel generative adversarial
network (GAN) for the task of unsupervised learning of 3D
representations from natural images.
Learn More
RenderNet: A Deep Conv. Network for
Differentiable Rendering from 3D Shapes
Traditional computer graphics rendering
pipelines are designed for procedurally generating 2D images from 3D
shapes with high performance.
Learn
More
Adversarial Monte Carlo Denoising with
Conditioned Aux. Feature Modulation
Denoising Monte Carlo rendering with a
very low sample rate remains a major challenge in the photo-realistic
rendering research.
Learn More
