Lambda Dual

Deep Learning Workstation with 2 GPUs

GPU workstation with two RTX 2080 Ti, Titan RTX, 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 Dual, a Deep Learning Workstation with 2x 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.

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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 Dual Basic, a GPU Workstation with 2x RTX 2080 Ti

2x RTX 2080 Ti

In Stock
2-Way NVLink
Intel i9-9820X CPU (10 Cores)
64 GB Memory
2 TB NVMe (3,500 MB/s Read)
$ 5,902
Customize
Premium
Lambda Dual Premium, a GPU Workstation with 2x Titan RTX

2x Titan RTX

In Stock
2-Way NVLink
Intel i9-9820X CPU (10 Cores)
128 GB Memory
2 TB NVMe (3,500 MB/s Read)
$ 9,646
Customize
Max
Lambda Dual Max, a GPU Workstation with 2x Quadro RTX 8000

2x Quadro RTX 8000

In Stock
2-Way NVLink
Intel i9-9980XE CPU (18 Cores)
128 GB Memory
2 TB NVMe (3,500 MB/s Read)
$ 18,004
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