GPU workstation for deep learning
Up to four fully customizable NVIDIA GPUs. Pre-installed with Ubuntu, TensorFlow, PyTorch®, CUDA, and cuDNN.
10,000+ research teams trust Lambda
Plug in. Start training.
Our workstations include Lambda Stack, which manages frameworks like PyTorch® and TensorFlow. With Lambda Stack, you can stop worrying about broken GPU drivers and focus on your research.
Zero configuration requiredAll your favorite frameworks come pre-installed.
Easily upgrade PyTorch® and TensorFlowWhen a new version is released, just run a simple upgrade command.
No more broken GPU driversDrivers will "just work" and keep compatible with popular frameworks.
Lambda Premium Support
With our Premium Support option, you can focus on your code and leave the rest to us. If something goes wrong with your machine, whether it be a driver issue, kernel panic, or hardware failure, our support team can debug it.
Expert assistanceFrom engineers ready to troubleshoot your hardware, operating system, and machine learning software.
Extra coverAn extended warranty covering hardware failures with rapid repair and replacement.
Always hereProviding you with live help from a dedicated contact via phone or email.
Explore our research
Multiple Pairwise Ranking Networks for Personalized Video Summarization
We propose a model for personalized video summaries by conditioning the summarization process with predefined categorical labels.
HoloGAN: Unsupervised Learning of 3D Reps. from Natural Images
We propose a novel generative adversarial network (GAN) for the task of unsupervised learning of 3D representations from natural images.
RenderNet: A Deep ConvNet for Differentiable Rendering from 3D Shapes
We present a differentiable rendering convolutional network with a novel projection unit that can render 2D images from 3D shapes.
Adversarial Monte Carlo Denoising with Conditioned Aux. Feature Modulation
We demonstrate that GANs can help denoiser networks produce more realistic high-frequency details and global illumination.
Up to 4 dual-slot PCIe GPUs. Options include:
- NVIDIA GeForce RTX 4090: 24 GB of GDDR6X, 16,384 CUDA cores, 512 Tensor Cores, PCIe 4.0 x16
- NVIDIA RTX 6000 Ada: 48 GB of GDDR6X, 18,176 CUDA cores, 568 Tensor Cores, PCIe 4.0 x16
- NVIDIA RTX A6000: 48 GB of GDDR6, 10,752 CUDA cores, 336 Tensor Cores, PCIe 4.0 x16
- NVIDIA RTX A5500: 24 GB of GDDR6, 10,240 CUDA cores, 320 Tensor Cores, PCIe 4.0 x16
- NVIDIA RTX A5000: 24 GB of GDDR6, 8,192 CUDA cores, 256 Tensor Cores, PCIe 4.0 x16
- NVIDIA RTX A4500: 20 GB of GDDR6, 7,168 CUDA cores, 224 Tensor Cores, PCIe 4.0 x16
- NVIDIA RTX A4000: 16 GB of GDDR6, 6,144 CUDA cores, 192 Tensor Cores, PCIe 4.0 x16
- Width: 13.1" (332 mm)
- Height: 16.3" (415 mm)
- Depth: 18.4" (458 mm)
- Weight: 38 pounds (17.2 kg)