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What is OpenVINO?

The Intel® Distribution of OpenVINO™ toolkit is an open-source resource for AI development that accelerates inference across a variety of Intel hardware. Designed to optimize AI workflows, this toolkit empowers developers to create sophisticated deep learning models for uses in computer vision, generative AI, and large language models. It comes with built-in model optimization features that ensure high throughput and low latency while reducing model size without compromising accuracy. OpenVINO™ stands out as an excellent option for developers looking to deploy AI solutions in multiple environments, from edge devices to cloud systems, thus promising both scalability and optimal performance on Intel architectures. Its adaptable design not only accommodates numerous AI applications but also enhances the overall efficiency of modern AI development projects. This flexibility makes it an essential tool for those aiming to advance their AI initiatives.

What is Mirai?

Mirai stands out as a sophisticated platform designed specifically for developers, focusing on on-device AI infrastructure that facilitates the conversion, optimization, and execution of machine learning models right on Apple devices, all while prioritizing performance and user privacy. With a streamlined workflow, teams can effectively convert and quantize models, evaluate their performance, distribute them, and perform local inference without any hassle. Tailored for Apple Silicon, Mirai aims to deliver near-zero latency and eliminate inference costs, ensuring that the processing of sensitive data remains entirely on the user's device for enhanced security. Its comprehensive SDK and inference engine empower developers to quickly embed AI capabilities into their applications, utilizing hardware-aware optimizations to fully harness the potential of the GPU and Neural Engine. Additionally, Mirai incorporates dynamic routing features that smartly decide on the optimal execution path for tasks, whether it be executing locally or accessing cloud resources, while considering important factors like latency, privacy, and workload requirements. This adaptability not only improves the overall user experience but also equips developers with the tools to craft more responsive and efficient applications that cater specifically to the needs of their users, ultimately driving innovation in the realm of on-device AI.

Media

Media

Integrations Supported

Caffe
Cameralyze
EndoAim
Gemma 3
Gemma 4
Intel Geti
Intel Open Edge Platform
Keras
LFM-3B
LaunchX
Llama
Nero AI
Nutanix Karbon Platform Services
ONNX
PaddlePaddle
PyTorch
Qwen3
SmolLM2
TensorFlow
gpt-oss-120b

Integrations Supported

Caffe
Cameralyze
EndoAim
Gemma 3
Gemma 4
Intel Geti
Intel Open Edge Platform
Keras
LFM-3B
LaunchX
Llama
Nero AI
Nutanix Karbon Platform Services
ONNX
PaddlePaddle
PyTorch
Qwen3
SmolLM2
TensorFlow
gpt-oss-120b

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Intel

Date Founded

1968

Company Location

United States

Company Website

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

Company Facts

Organization Name

Mirai

Date Founded

2024

Company Location

United States

Company Website

trymirai.com

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Categories and Features

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