Lambda Quad

Deep Learning Workstation with 4 GPUs

GPU workstation with four RTX 2080 Ti, RTX 5000, RTX 6000, or RTX 8000 GPUs. Pre-installed with Ubuntu, TensorFlow, PyTorch, Keras, CUDA, and cuDNN, so you can boot up and start training immediately.

Lambda Quad, a Deep Learning Workstation with 4x GPUs

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.

Apple is a customer MIT is a customer Los Alamos National Lab is a customer Carnegie Mellon University is a customer Google is a customer Wells Fargo is a customer Anthem is a customer

Recommended Designs

Optimized configurations that won't bottleneck

Our recommended designs are benchmarked and tuned to eliminate CPU, memory, and storage bottlenecks when running deep learning workloads.

Basic
Lambda Quad Basic, a GPU Workstation with 4x RTX 2080 Ti

4x RTX 2080 Ti

In Stock
Intel i9-9820X CPU (10 Cores)
64 GB Memory
2 TB NVMe (3,500 MB/s Read)
$ 8,449
Customize
Premium
Lambda Quad Premium, a GPU Workstation with 4x Quadro RTX 6000 GPUs

4x Quadro RTX 6000

In Stock
Intel i9-9920X CPU (12 Cores)
128 GB Memory
2 TB NVMe (3,500 MB/s Read)
$ 20,657
Customize
Max
Lambda Quad Max, a GPU Workstation with 4x Quadro RTX 8000 GPUs

4x Quadro RTX 8000

In Stock
Intel W-2195 CPU (18 Cores)
256 GB Memory
2 TB NVMe (3,500 MB/s Read)
$ 31,535
Customize
Custom

In Stock
+1 (866) 711-2025
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Fully Customizable

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.

Zero setup, easy updates

Lambda Stack comes free with your computer. Machine Learning libraries work out-of-the box and can be updated automatically.

Ubuntu 18.04 comes pre-installed
TensorFlow comes pre-installed
PyTorch comes pre-installed
Keras comes pre-installed

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