Backed by expert support from DL engineers.
Faster hardware tightens the feedback loop on your choice of network architecture, loss function, and other hyperparameters. Investing in proper hardware saves you hundreds of hours. Your time is worth it.
Faster hardware gets you to market quicker. The impact is significant. In 2017, Facebook reduced their training duration from 29 hours to 1 hour with a hardware upgrade.
Many of our team members come from Deep Learning research backgrounds. We know the clock is always ticking. Grants run out. You need to reduce the duration of your experiments from days to hours.
A rapid feedback loop provides students with a faster pace of learning. Help them make the most of their education.
If you're looking for an enterprise solution for cutting-edge Deep Learning performance and parallelization, the Lambda Blade is a necessity. Experience how profitable of an investment Deep Learning hardware can be for your team.
Designed for deployment in data centers, our 8 GPU configurations significantly boost Deep Learning performance and are ideal for remote access from multiple concurrent users.
QUAD is our most powerful and most popular workstation. It delivers significant speed improvements for all applications.
If you’re part of a research group, the Lambda QUAD allows multiple engineers to work simultaneously to significantly increase development productivity.
SINGLE is an introduction to high performance Deep Learning hardware. Pre-installed is every framework you’ll need — including Tensorflow, Torch, and Caffe.
The SINGLE is the perfect option for hobbyist Deep Learning dev that doesn't need their workstation accessible by a team.
We rent access to our cloud-based workstations on a month-to-month basis. It scales with your needs. State-of-the-art deep learning GPUs at the most affordable prices on Earth. Save thousands switching from AWS.
Our salespeople are engineers. When you chat with us, there's no sales talk. We're a small team of experts who take pride in our machines.
Call us. Tell us what you're working on, and we'll talk you through your options.