Lambda Launches World's Most Powerful Ubuntu Linux Laptop for Deep Learning

Lambda, a provider of deep learning infrastructures, has teamed up with Razer, the world’s leading lifestyle brand for gamers, to build a Linux-powered laptop for deep learning.

Meet Razer x Lambda Tensorbook, the world’s most powerful Ubuntu Linux laptop designed for deep learning. Powered by an Intel i7-11800 Octo-Core processor featuring up to 4.6GHz clock speeds and an NVIDIA GeForce RTX 3080 Max-Q graphics card with 16GB VRAM, the Tensorbook laptop provides ML engineers an all-in-one deep learning solution for all their needs.

For that, the Tensorbook laptop comes with the Lambda GPU Cloud service and the full Lambda Stack, which includes software like NVIDIA CUDA, cuDNN, PyTorch, TensorFlow, Keras, Caffe, Caffe 2, as well as the NVIDIA drivers and various other useful Linux tools like build-essential, GNU Emacs, Git, htop, GNU Screen, tmux, Valgrind, and Vim.

“Most ML engineers don’t have a dedicated GPU laptop, which forces them to use shared resources on a remote machine, slowing down their development cycle,” said Stephen Balaban, Lambda CEO and co-founder. “When you’re stuck SSHing into a remote server, you don’t have any of your local data or code and even have a hard time demoing your model to colleagues. The Razer x Lambda Tensorbook solves this.”

Design-wise, the Linux laptop looks sleek with its slim 2.1 kg (4.43 lbs) aluminum unibody chassis, as you can see from the video below, and features a 15.6-inch 2K (2560x1440p) 165Hz display. Under the hood, it features high-performance hardware from Razer, including up to 64GB 3200 MHz DDR4 memory, 2 TB NVMe PCIe 4.0 SSD storage, and Thunderbolt 4 (2xUSB Type-C ports) support.

The Razer x Lambda Tensorbook is available to order today from lambdalabs.com, starting at $3,499 USD. It comes pre-installed with the Ubuntu 20.04 LTS (Focal Fossa) operating system, but it can be configured to dual boot with Microsoft Windows too. The notebook comes with one year of Lambda engineering support and warranty.

Image credits: Lambda (edited by Marius Nestor)

Last updated 1 year ago