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Average Ratings 0 Ratings

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ease
features
design
support

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Description

The Intel® Distribution of OpenVINO™ toolkit serves as an open-source AI development resource that speeds up inference on various Intel hardware platforms. This toolkit is crafted to enhance AI workflows, enabling developers to implement refined deep learning models tailored for applications in computer vision, generative AI, and large language models (LLMs). Equipped with integrated model optimization tools, it guarantees elevated throughput and minimal latency while decreasing the model size without sacrificing accuracy. OpenVINO™ is an ideal choice for developers aiming to implement AI solutions in diverse settings, spanning from edge devices to cloud infrastructures, thereby assuring both scalability and peak performance across Intel architectures. Ultimately, its versatile design supports a wide range of AI applications, making it a valuable asset in modern AI development.

Description

Accelerate the building, training, and deployment of models at scale through a fully managed infrastructure that provides essential tools and streamlined workflows. Launch personalized AI and LLMs on any infrastructure in mere seconds, effortlessly scaling inference as required. Tackle your most intensive tasks with batch job scheduling, ensuring you only pay for what you use on a per-second basis. Reduce costs effectively by utilizing GPU resources, spot instances, and a built-in automatic failover mechanism. Simplify complex infrastructure configurations by deploying with just a single command using YAML. Adjust to demand by automatically increasing worker capacity during peak traffic periods and reducing it to zero when not in use. Release advanced models via persistent endpoints within a serverless architecture, maximizing resource efficiency. Keep a close eye on system performance and inference metrics in real-time, tracking aspects like worker numbers, GPU usage, latency, and throughput. Additionally, carry out A/B testing with ease by distributing traffic across various models for thorough evaluation, ensuring your deployments are continually optimized for performance.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) No 
Caffe Yes 
Cameralyze Yes 
EndoAim Yes 
FLUX.1 No 
Gemma No 
Gemma 2 No 
Google Cloud Platform No 
Intel Geti Yes 
Intel Open Edge Platform Yes 
Kubernetes No 
LangChain No 
Llama 3 No 
Mixtral 8x7B No 
MusicGen No 
Nero AI Yes 
ONNX Yes 
OpenAI Whisper No 
TensorFlow Yes 
Visual Studio Code No 

Integrations

Amazon Web Services (AWS) Yes 
Caffe No 
Cameralyze No 
EndoAim No 
FLUX.1 Yes 
Gemma Yes 
Gemma 2 Yes 
Google Cloud Platform Yes 
Intel Geti No 
Intel Open Edge Platform No 
Kubernetes Yes 
LangChain Yes 
Llama 3 Yes 
Mixtral 8x7B Yes 
MusicGen Yes 
Nero AI No 
ONNX No 
OpenAI Whisper Yes 
TensorFlow No 
Visual Studio Code Yes 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

$100 + compute/month
Free Trial No 
Free Version Yes 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Intel

Founded

1968

Country

United States

Website

www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/overview.html

Vendor Details

Company Name

VESSL AI

Founded

2020

Country

United States

Website

vessl.ai/

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

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