We understand every development environment is different, so shouldn't you have the option to choose what's best for you? All EMLI (Exxact Machine Learning Images) environments are available in the latest Ubuntu or CentOS Linux versions, and are built to perform right out of the box.
Multi-GPU Performance
Leverage the latest NVIDIA GPUs including the RTX 3090/3080/3070, RTX A6000, RTX A5000, TITAN RTX, and more to accelerate AI development.
Pre-Installed Frameworks
Our systems come pre-loaded with TensorFlow, PyTorch, Keras, Caffe, RAPIDS, Docker, Anaconda, MXnet and more upon request.
Standard 3 Year Warranty
Have peace of mind, focus on what matters most, knowing your system is backed by a 3 year warranty and support.
AI Workstations for Any Workload
NVIDIA AI Workstations

The industry-standard deep learning workstation, engineered to meet any budget.
AMD Ryzen AI Workstations

Powerful GPU workstations featuring 3rd Generation AMD Ryzen Threadripper CPUs.
Data Science Workstations

Transform massive amounts of data into insights with an NVIDIA-powered data science workstation.
NVIDIA DGX Station

Designed for your office environment, and built on the same software stack powering all NVIDIA DGX systems.
Exxact Machine Learning Images
Preinstalled Developer-Ready Environment
Find Your Perfect Deep Learning Environment with EMLI
Most Popular | |||
Compare*Additional NGC (NVIDIA GPU Cloud) containers can be added upon request. | Conda EMLISeparated Frameworks | Container EMLIFlexible. Reconfigurable. | DIY EMLISimple. Clean. Custom. |
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Who is it for? | For developers who want pre-installed deep learning frameworks and their dependencies in separate Python environments installed natively on the system. | For developers who want pre-installed frameworks utilizing the latest NGC containers, GPU drivers, and libraries in ready to deploy DL environments with the flexibility of containerization. | For experienced developers who want a minimalist install to set up their own private deep learning repositories or custom builds of deep learning frameworks. |
Frameworks* | |||
TensorFlow V1 | — | — | |
TensorFlow V2 | — | ||
PyTorch | — | ||
MXnet | — | ||
Caffe | — | — | |
Caffe2 | — | ||
Chainer | — | — | |
Microsoft Cognitive Toolkit | — | — | |
Libraries* | |||
NVIDIA cuDNN | |||
NVIDIA Rapids | — | ||
Keras | — | ||
Theano | — | ||
OpenCV | — | ||
Software Environments | |||
NVIDIA CUDA Toolkit | |||
NVIDIA CUDA Dev Toolkit | — | ||
NVIDIA Digits | — | ||
Anaconda | — | ||
Container Management | |||
Docker | — | ||
Drivers | |||
NVIDIA-qualified Driver | |||
Orchestration | |||
Micro-K8s | Free upgrade available | Free upgrade available | Free upgrade available |
Deep Learning Lifecycle
NVIDIA Powered Data Center Platforms
Training
With deep neural networks becoming more complex, training times have increased dramatically, resulting in lower productivity and higher costs. Exxact's deep learning infrastructure technology featuring NVIDIA GPUs significantly accelerates AI training, resulting in deeper insights in less time, significant cost savings, and faster time to ROI.
ExploreInference
Data center managers must make tradeoffs between performance and efficiency. A single inference server from Exxact can replace multiple commodity CPU servers for deep learning inference applications and services, reducing energy requirements and delivering both acquisition and operational cost savings.
Explore
Accelerate Deep Learning Initiatives
NVIDIA DGX™ A100
The universal system for all AI workloads, offering unprecedented compute density, performance and flexibility in the world’s first 5 petaFLOPS AI system. Order yours today.

Partnered with Leaders in Innovation
