New!
Cloud GPU servers from $1.25 per hour
GPU laptop built for deep learning
Powered by the NVIDIA RTX 2080 Super Max-Q GPU. Pre-installed with TensorFlow, PyTorch, Keras, CUDA, and cuDNN and more.
Customize now
1000+ research groups trust Lambda







Easy system administration
Our deep learning laptop comes with Lambda Stack, which includes frameworks like TensorFlow, PyTorch, and Keras. Lambda Stack makes upgrading these frameworks easy.





I/O port overview
Kensington lock slot
MicroSD
3.5 mm headphone + mic

USB 3 (powered)
3.5mm mic + S/PDIF
USB 3
USB 3
HDMI
Thunderbolt 3

Gigabit ethernet (RJ45)
Technical specifications
GPU
RTX 2080 Super Max-Q
8 GB GDDR6, 3072 CUDA cores, 1080 MHz base clock
Processor
8 cores, 2.30 GHz
Intel Core i7-10875H with 16 threads, 5.10 GHz turbo, and 16 MB cache
Memory
64 GB
of 2666 MHz DDR4 SO-DIMM
Storage
2 TB
Samsung 970 EVO with 1 TB, 3,500 MB/s seq. read, 2,500 MB/s seq. write
Samsung 860 EVO with 1 TB, 550 MB/s seq. read, 520 MB/s seq. write
Size & weight
Width:
14.07" (357 mm)
Height:
0.78" (20 mm)
Depth:
9.37" (238 mm)
Weight:
4.39 lbs (2 kgs)
Display
15.6"
1920x1080 (Full HD), 144 Hz, Matte, 72% NTSC
Audio ports
1x 3.5mm 2-in-1 audio jack (headphone + microphone)
1x 3.5mm 2-in-1 audio jack (microphone + S/PDIF optical)
Video ports
1x HDMI with HDCP
1x Mini DisplayPort 1.4
1x Thunderbolt 3
USB ports
2x USB 3.2 Gen 1 Type A
1x powered (AC/DC) USB 3.2 Gen 1 Type A
Networking
Ethernet:
1x 10/100/1000 Mbps RJ45 port
Wireless:
Intel Dual Band WiFi 6 AX
Bluetooth:
Supported
Power
Battery:
73 watt-hour embedded 3-cell polymer battery pack
Power adapter:
AC in, DC out. Output: 180 watts, 19.5 volts, 9.23 amps
Power input requirements:
100 to 240 VAC at 50 to 60 Hz
Frequently asked questions
Not seeing the answer to your question? Contact sales
What if my laptop develops a hardware issue?
Lambda offers perpetual support from our engineers and up to 3 years of
warranty. If you experience issues with your TensorBook, our engineers
are available by email at support@lambdalabs.com and by
phone at +1 (855) 882-6011. We will
immediately replace any faulty components (e.g. GPU, CPU, battery),
which you may return at your convenience. If your TensorBook is still
under warranty, all replacements will be free of charge. Solutions to
technical issues may also be found within our community, Deep Talk.
Why is there no 4K (Ultra HD) display option?
In short: battery life. Rendering a 4K display is extremely costly from
a power perspective. For most people a longer battery life is more
important than a higher resolution display.
Are discounts available for academics or students?
Yes, we offer a 3% discount on TensorBooks for academics and
students. To get your discount, email us at enterprise@lambdalabs.com or
by phone at +1 (866) 711-2025.
Are discounts available for bulk purchases?
Yes, we offer bulk discounts. Pricing will depend on project size. For
details, please contact us by email at enterprise@lambdalabs.com or
by phone at +1 (866) 711-2025.
How long will it take for my laptop to ship?
Your TensorBook will typically ship within 1 to 3 business days after purchase.
Does Lambda offer shipping to countries outside the United States?
Yes, Lambda ships globally. Please note if you're outside the United
States, your order may be subject to duties and tariffs. For more
information, please contact our sales team.
What operating systems are available for the TensorBook?
The TensorBook can be pre-installed with either Ubuntu 18.04, Ubuntu 16.04, or Windows
10 Pro.
Does Lambda offer dual booting of operating system?
Yes, we can dual boot your TensorBook with Windows 10 Pro and Ubuntu
18.04. For more details, please contact us by email at enterprise@lambdalabs.com or
by phone at +1 (866) 711-2025.
What payment methods are accepted?
We accept wire transfers, ACH transfers, and credit cards. Please note
that credit card transactions are subject to an additional 3% charge.
Explore our research
Lambda's research papers have been accepted into the top machine learning and graphics conferences, including ICCV, SIGGRAPH Asia, NeurIPS, and ACM Transactions on Graphics (TOG).




HoloGAN: Unsupervised Learning of 3D
Representations from Natural Images
We propose a novel generative adversarial
network (GAN) for the task of unsupervised learning of 3D
representations from natural images.
Learn More
RenderNet: A Deep Conv. Network for
Differentiable Rendering from 3D Shapes
Traditional computer graphics rendering
pipelines are designed for procedurally generating 2D images from 3D
shapes with high performance.
Learn
More
Adversarial Monte Carlo Denoising with
Conditioned Aux. Feature Modulation
Denoising Monte Carlo rendering with a
very low sample rate remains a major challenge in the photo-realistic
rendering research.
Learn More
