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Azure OpenAI vs Hugging Face comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Apr 20, 2025

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
7.8
Reviews Sentiment
6.7
Number of Reviews
33
Ranking in other categories
No ranking in other categories
Hugging Face
Ranking in AI Development Platforms
4th
Average Rating
8.2
Reviews Sentiment
7.1
Number of Reviews
13
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2025, in the AI Development Platforms category, the mindshare of Azure OpenAI is 12.9%, down from 21.1% compared to the previous year. The mindshare of Hugging Face is 13.5%, up from 7.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms
 

Featured Reviews

Viswanath Barenkala - PeerSpot reviewer
Offers tools to moderate generated content and guidance to safely design applications, but it is not consistently accessible
Instead of a feature, the GPT-4 model has been most beneficial for automating tasks. We transitioned from GPT-3.5 to GPT-4 and actively use it. However, we face limitations due to geographic availability, subscription constraints, and rate limiting, which we are currently negotiating and working towards optimizing. While we haven't formally benchmarked Azure OpenAI's language understanding against industry standards, we find it performs well about 70-80% of the time. Occasionally, we need to refine our queries and adapt our systems accordingly to improve accuracy and effectiveness.
SwaminathanSubramanian - PeerSpot reviewer
Versatility empowers AI concept development despite the multi-GPU challenge
Regarding scalability, I'm finding the multi-GPU aspect of it challenging. Training the model is another hurdle, although I'm only getting into that aspect currently. Organizations are apprehensive about investing in multi-GPU setups. Additionally, data cleanup is a challenge that needs to be resolved, as data must be mature and pristine.

Quotes from Members

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

Pros

"Azure's integration with OpenAI's GPT is beneficial as well, especially for text generation tasks."
"I would rate it a nine out of ten."
"The product is easy to integrate with our IT workflow."
"GPT was useful for our projects."
"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."
"The AI search functionality is particularly effective, as it creates summaries from data."
"Azure OpenAI has significantly reduced costs and increased efficiency in tasks such as aggressive testing of systems to avoid anomalies and trust issues."
"Two aspects I appreciate are the turnaround time and ease of use. As it's a managed service, the quick turnaround is beneficial, and the simple interface makes it easy to work with. Performance and scalability are also strong points since you can scale as needed."
"What I find the most valuable about Hugging Face is that I can check all the models on it and see which ones have the best performance without using another platform."
"I appreciate the versatility and the fact that it has generalized many models."
"My preferred aspects are natural language processing and question-answering."
"It is stable."
"The product is reliable."
"The tool's most valuable feature is that it shows trending models. All the new models, even Google's demo models, appear at the top. You can find all the open-source models in one place. You can use them directly and easily find their documentation. It's very simple to find documentation and write code. If you want to work with AI and machine learning, Hugging Face is a perfect place to start."
"Overall, the platform is excellent."
"I would rate this product nine out of ten."
 

Cons

"Azure OpenAI will be expensive if you want to implement it as a permanent solution for a customer."
"Azure OpenAI should use more specific sources like academic articles because sometimes the source can't be found."
"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."
"We encountered challenges related to question understanding."
"There are certain shortcomings with the product's scalability and support team where improvements are required."
"The dialogue manager needs to be improved."
"The fine-tuning of models with the use of Azure OpenAI is an area with certain shortcomings currently, and it can be considered for improvement in the future."
"One major drawback of Azure OpenAI is its availability, as it's not consistently accessible for effective use."
"The initial setup can be rated as a seven out of ten due to occasional issues during model deployment, which might require adjustments."
"Access to the models and datasets could be improved. Many interesting ones are restricted."
"The solution must provide an efficient LLM."
"Initially, I faced issues with the solution's configuration."
"Hugging Face could improve by implementing a search engine or chat bot feature similar to ChatGPT."
"It can incorporate AI into its services."
"The area that needs improvement would be the organization of the materials. It could be clearer and more systematic. It would be good if the layout was clear and we could search the models easily."
"I've worked on three projects using Hugging Face, and only once did we encounter a problem with the code. We had to use another open-source embedding from OpenAI to resolve it. Our team has three members: me, my colleague, and a team leader. We looked at the problem and resolved it."
 

Pricing and Cost Advice

"It's a token-based system, so you pay per token used by the model."
"While the product meets our business requirements well, I consider it relatively expensive, especially for individual users like myself."
"The cost is pretty high. Even by US standards, you would find it high."
"The tool costs around 20 dollars a month."
"Azure OpenAI is a bit more expensive than other services."
"The solution's pricing is normal worldwide but expensive in Turkey because Turkey's currency is different."
"The platform offers a flexible pricing model which depends on the features and capabilities we utilize."
"I rate the product pricing six out of ten."
"So, it's requires expensive machines to open services or open LLM models."
"The tool is open-source. The cost depends on what task you're doing. If you're using a large language model with around 12 million parameters, it will cost more. On average, Hugging Face is open source so you can download models to your local machine for free. For deployment, you can use any cloud service."
"We do not have to pay for the product."
"I recall seeing a fee of nine dollars, and there's also an enterprise option priced at twenty dollars per month."
"Hugging Face is an open-source solution."
"The solution is open source."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
13%
Manufacturing Company
11%
Educational Organization
6%
Computer Software Company
11%
Financial Services Firm
11%
University
10%
Manufacturing Company
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Azure OpenAI?
The product is easy to integrate with our IT workflow.
What is your experience regarding pricing and costs for Azure OpenAI?
In the past, the primary expense involved token limitations which constrained scaling. Recent iterations have increased token allowances, mitigating some challenges associated with concurrent user ...
What needs improvement with Azure OpenAI?
Azure ( /products/microsoft-azure-reviews ) could significantly benefit from including more LLM models apart from OpenAI, as I often need to switch clouds when a model doesn't meet my requirements....
What do you like most about Hugging Face?
My preferred aspects are natural language processing and question-answering.
What needs improvement with Hugging Face?
Access to the models and datasets could be improved. Many interesting ones are restricted. It would be great if they provided access for students or non-professionals who just want to test things.
What is your primary use case for Hugging Face?
This is a simple personal project, non-commercial. As a student, that's all I do.
 

Overview

Find out what your peers are saying about Azure OpenAI vs. Hugging Face and other solutions. Updated: April 2025.
848,716 professionals have used our research since 2012.