Lambda Teams Up With Razer to Launch the World’s Most Powerful Laptop for Deep Learning
“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, co-founder and CEO of Lambda. “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. It’s pre-installed with PyTorch and TensorFlow and lets you quickly train and demo your models: all from a local GUI interface. No more SSH!”
An All-in-One Deep Learning Solution
The new Tensorbook comes pre-configured with a complete software environment from Lambda, including Ubuntu Linux with the Lambda Stack for training large workloads anytime, anywhere. The laptop features sleek, high-performance hardware from Razer, powered by NVIDIA RTX 3080, one of the most powerful mobile GPUs available for dedicated, uninterrupted compute at a moment’s notice and full compatibility with TensorFlow, PyTorch, cuDNN, CUDA, and other ML frameworks and tools.
“Razer’s experience in developing high performance products for both gamers and creators has been a crucial building block for the Lambda Tensorbook, a deep learning system for engineers,” said Travis Furst, Head of Razer’s Laptop Division. “The shared customer obsession is what drove us to collaborate with Lambda in developing this powerful, specialized device. We can’t wait to see the amazing breakthroughs that will be made by engineers and researchers while using a Tensorbook.”
Availability and Specifications
The new Tensorbook is available for order today from $3,499 at lambdalabs.com.
Specifications include:
Hardware
- 15.6″ 2560×1440 165 Hz display
- NVIDIA RTX 3080 Max-Q GPU with 16 GB VRAM
- Intel i7-11800 Processor (8 cores, 2.3 GHz to 4.6 GHz)
- 64 GB DDR4 memory
- 2 TB SSD storage
- Thunderbolt 4, USB 3.2, HDMI 2.1 ports
- Slim 4.4 lb aluminium unibody chassis
- 1080p webcam
Software
- Ubuntu Linux 20.04 LTS (Microsoft Windows dual boot optional)
- Lambda Stack with PyTorch, TensorFlow, CUDA, cuDNN, and NVIDIA Drivers
- One year of Lambda engineering support