Azure OpenAI vs OpenVINO comparison

Microsoft and Intel are both solutions in the AI Development Platforms category. Microsoft is ranked #1 with an average rating of 7.9, while Intel is ranked #14. Microsoft holds a 17.5% mindshare in AIDP, compared to Intel’s 1.8% mindshare. Additionally, 93% of Microsoft users are willing to recommend the solution, compared to 100% of Intel users who would recommend it.

Azure OpenAI

Read 32 Azure OpenAI reviews

8,535 Views
7,918 Comparison Views

93% willing to recommend

OpenVINO

Read 3 OpenVINO reviews

2,201 Views
1,241 Comparison Views

100% willing to recommend

Azure OpenAI

OpenVINO

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 4, 2024

OpenVINO and Azure OpenAI are products catering to machine learning performance optimization and large-scale language model capabilities, respectively. OpenVINO appears advantageous for edge device integration, while Azure OpenAI provides superior features for cloud-based AI applications.

Features: OpenVINO provides advanced model optimization, supports heterogeneous execution, and is optimal for real-time applications on edge devices. Azure OpenAI offers access to powerful AI models, cloud service integration, and comprehensive support for natural language processing.

Ease of Deployment and Customer Service: OpenVINO allows easy deployment on edge devices with diverse hardware support and benefits from community-driven support. Azure OpenAI simplifies deployment within Azure's ecosystem and provides professional support with thorough documentation, enhancing ease of use in cloud environments.

Pricing and ROI: OpenVINO offers a low-cost entry with free licensing and efficient resource usage for edge devices. Azure OpenAI involves higher setup costs but provides substantial ROI through enhanced productivity and scalability with cloud infrastructure.

To learn more, read our detailed Azure OpenAI vs. OpenVINO Report (Updated: January 2025).

Buyer's Guide

Azure OpenAI vs. OpenVINO

January 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Azure OpenAI

Ranking in AI Development Platforms

1st

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

OpenVINO

Ranking in AI Development Platforms

14th

Average Rating

8.6

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2025, in the AI Development Platforms category, the mindshare of Azure OpenAI is 17.5%, down from 19.2% compared to the previous year. The mindshare of OpenVINO is 1.8%, down from 3.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AI Development Platforms

Featured Reviews

Anup Karade

Associate Vice President at LTIMindtree

Created a chatbot powered by OpenAI to answer HR, travel, and expense-related questions

We have created our own platform called CanvasAI. It provides machine-learning plumbing and integration with your services. So, we've integrated Azure OpenAI through Canvas. We're also looking at some hard interface modeling from AWS as well. We access Azure OpenAI solutions for our business workflow via the platform, not directly from the service provider. There are security considerations we're working through with the security team, etc. Canvas provides the control plane, which handles RBAC for user registration and model management. For internal processes, we're using OpenAI to create partner call reports, like summarizing quarterly zip code data and other financial models. We also use it for legal and contract stuff, like comparing SOWs and contracts. For user experience, we've created a chatbot powered by OpenAI to answer HR, travel, and expense-related questions.

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reviewer1530384

Systems and Solutions Architect at a tech services company with 1,001-5,000 employees

Open-source, easy to integrate, and perfectly tailored to the Movidius chipset

Generally, when you deploy edge products, it's really about latency. It's about getting that camera input, being able to process it, extracting the information you need, and getting the solution back to the person who made the request. Although I'm not necessarily saying its latency or accuracy is bad, it's always something that can be improved upon. By focusing on improving these areas, they can make the overall solution even better. At this point, the product could probably just use a greater integration with more machine learning model tools. However, that's not advice from experience per se. That's always just helpful in general. To be able to incorporate more models into the product makes it stronger. Therefore, to be clear, it's not coming from a point of a current deficiency. It's just a general comment.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The product is easy to integrate with our IT workflow."

"I would rate it a nine out of ten."

"OpenAI integrates seamlessly with the broader Microsoft Azure ecosystem, and that provides synergies with the other solutions. This integration makes it much easier to build solutions."

"Azure OpenAI is very easy to use instead of AWS services."

"Azure OpenAI is useful for benchmarking products."

"The AI search functionality is particularly effective, as it creates summaries from data."

"The most crucial aspect is the conversational capability, where you can simply ask questions, and it provides answers based on your content and documents, particularly tailored to your specific environment."

"It's very powerful. It allows users to query our documents using natural language and receive answers in the same way. This makes our product information much more accessible than traditional keyword-based search."

More Azure OpenAI pros

"The inferencing and processing capabilities are quite beneficial for our requirements."

"The features for model comparison, the feature for model testing, evaluation, and deployment are very nice. It can work almost with all the models."

"The initial setup is quite simple."

Cons

"Azure OpenAI will be expensive if you want to implement it as a permanent solution for a customer."

"The product features themselves are fine. However, with Microsoft scaling the service so much, the support structure needs to keep pace. When solving complex issues, the process of interacting with Microsoft can be quite time-consuming."

"Azure needs to work on its own model development and improve the integration of voice-to-text services, particularly for right-to-left languages such as Arabic and Urdu."

"The solution's response is a bit slow sometimes."

"I noticed there are no instructional videos or guides on the network portal for initial configurations. There is limited information available, and this is a concern for me. I would like to see more resources and guides to address these issues."

"The dialogue manager needs to be improved."

"The UI could be a little easier."

"Azure OpenAI is not available in all regions, and its technical support should be improved."

More Azure OpenAI cons

"The model optimization is a little bit slow — it could be improved."

"At this point, the product could probably just use a greater integration with more machine learning model tools."

"It has some disadvantages because when you're working with very complex models, neural networks if OpenVINO cannot convert them automatically and you have to do a custom layer and later add it to the model. It is difficult."

Pricing and Cost Advice

"The solution's pricing depends on the services you will deploy."

"We started with monthly payments, but we plan to switch to yearly billing once we've stabilized our solution."

"The cost structure depends on the volume of data processed and the computational resources required."

"Regarding pricing and licensing, it's a bit complex due to the minimum purchase requirement for PTO units. We're evaluating the best approach between PTE and pay-as-you-go models. Our organization is cautious about committing to PTE due to the fixed bandwidth reservation, while pay-as-you-go doesn't offer enough flexibility. We're discussing these matters with legal teams to ensure compliance and data security."

"I'm uncertain about the licensing, specifically the pricing. This falls under the purview of other teams, particularly the sales teams. I am not informed about the pricing details."

"The cost is quite high and fixed."

"It's a token-based system, so you pay per token used by the model."

"Azure OpenAI is a bit more expensive than other services."

More Azure OpenAI pricing and cost advice

"We didn't have to pay for any licensing with Intel OpenVINO. Everything is available on their site and easily downloadable for free."

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Computer Software Company

13%

Manufacturing Company

11%

Educational Organization

Manufacturing Company

46%

University

Computer Software Company

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about Azure OpenAI?

The product is easy to integrate with our IT workflow.

See all answers

What is your experience regarding pricing and costs for Azure OpenAI?

The pricing is very good for handling various kinds of jobs. While small jobs are manageable, more complex jobs require a higher model, which is a bit challenging.

See all answers

What needs improvement with Azure OpenAI?

Maybe with the next release, the response will be more precise and more human-like.

See all answers

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Comparisons

Google Vertex AI vs Azure OpenAI

Compared 46% of the time

Amazon SageMaker vs Azure OpenAI

Compared 11% of the time

Hugging Face vs Azure OpenAI

Compared 11% of the time

Microsoft Azure Machine Learning Studio vs Azure OpenAI

Compared 9% of the time

Together Inference vs Azure OpenAI

Compared 1% of the time

More Azure OpenAI Competitors

TensorFlow vs OpenVINO

Compared 56% of the time

PyTorch vs OpenVINO

Compared 22% of the time

Google Vertex AI vs OpenVINO

Compared 8% of the time

More OpenVINO Competitors

Product Reports

Buyer's Guide

Azure OpenAI

January 2025

Download Azure OpenAI product report

Buyer's Guide

OpenVINO

January 2025

Download OpenVINO product report

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Microsoft

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Intel

Overview

Azure OpenAI integrates advanced language models with robust security for precise information extraction and task automation. Its seamless Azure integration and drag-and-drop interface simplify implementation and enhance accessibility.

Azure OpenAI offers a comprehensive suite of features designed for efficient data processing and task automation. It provides high precision in extracting information and strong conversational capabilities, crucial for developing chatbots and customer support systems. Its integration with Azure ensures seamless data handling and security, addressing key enterprise requirements. Users can employ its versatile GPT models for diverse applications such as predictive analytics, summarizing large documents, and competitive benchmarking. Despite its strengths, it faces challenges like latency, inadequate regional support, and limited integration of new technologies. Improvements in model fine-tuning and more flexible configuration are desired by users.

What features make Azure OpenAI a reliable choice?

High Precision: Ensures accurate data extraction suitable for critical applications.
Conversational Capabilities: Facilitates the creation of sophisticated chatbots.
Azure Integration: Seamlessly connects with Azure services for enhanced functionality.
Automation Support: Automates repetitive tasks, improving efficiency.
Security Features: Offers robust protection for sensitive data.
Drag-and-Drop Environment: Simplifies user interaction and deployment.

What benefits and ROI should users consider?

Natural Language Processing: Provides superior language model performance.
Quick Implementation: Reduces time to deploy applications.
Scalability: Supports growing business needs with ease.
Versatile GPT Models: Applicable across different industry workflows.

Azure OpenAI is implemented across industries like healthcare, finance, and education for tasks like invoice processing, digitalizing records, and language translation. It enhances policy management, document assimilation, and customer support with predictive analytics and keyword extraction. Organizations in such sectors benefit from streamlined workflows and task automation.

OpenVINO toolkit quickly deploys applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNNs), the toolkit extends computer vision (CV) workloads across Intel hardware, maximizing performance. The OpenVINO toolkit includes the Deep Learning Deployment Toolkit (DLDT).

Buyer's Guide

Azure OpenAI vs. OpenVINO

January 2025

Free Report: Azure OpenAI vs. OpenVINO

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