Razer Lambda Tensorbook, the most powerful Linux laptop for Deep-learning

he most powerful Linux laptop

The supply of devices and computers with an operating system based on Linux or Linux itself pre-installed is growing every day. Not only in computers with low performance, they are also beginning to be very present in high-end ones, made with a specific purpose.

This is the case of the Razer X Lambda Tensorbook , a high-end laptop with great features that we are here to talk about today. This super powerful laptop is intended to be used for Deep Learning or Data Science.

In fact, it is characterized by its Intel processor and dedicated graphics with an Nvidia GPU, all managed from an Ubuntu operating system.

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Although Razer is better known for being a company much more focused on the world of video games, it takes a risk with this ambitious proposal aimed at software engineers who choose the field of Deep Learning. One of the most demanding fields in terms of hardware is concerned, to be able to process data at a higher speed.

In this the Razer X Lambda Tensorbook aspires to be one of the best, let’s see a little more in detail the software specifications that it brings with it:

  • Intel i7 processor with eight cores and 16 threads at 2.30GHz and a turbo of 4.60Ghz.
  • 15.4-inch IPS screen
  • Nvidia GeForce RTX 3080 MaxQ Graphics.
  • 64Gb de RAM DDR3 a 3200 MHz
  • 2TB capacity SSD storage

In terms connectivity , it is also quite complete, since we find:

  • Puerto Thunderbolt 4
  • Puerto USB 3.2
  • Puerto HDMI 2.1
Razer Lambda Tensorbook, the most powerful Linux laptop for Deep-learning

With dimensions of 16.9 x 355 x 235 mm and weighing approximately 2.1 Kg, it is very manageable for everything it offers us.

The inconvenient? the price, since it ranges from 3,500 dollars to almost touch 5,000 dollars in its version with more features.

However, it can be a great investment for all those Machine Learning engineers to be able to have a laptop with dedicated graphics and enough resources and rule out the need to hire cloud services to work on a day-to-day basis wherever they are. It already comes with resources like Pytorch or Tensorflow installed so you can start training your models from minute one.

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