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Azure OpenAI vs Hugging Face comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 12, 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
7.0
Number of Reviews
12
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

"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."
"Azure OpenAI is used as chat services, allowing me to replace human tasks with analytical capabilities."
"Azure OpenAI is easy to use because the endpoints are created, and we just need to pass our parameters and info."
"Generative AI or GenAI seems to be the best part of the solution."
"Azure OpenAI is useful for benchmarking products."
"The most valuable feature of Azure OpenAI stems from the GPT-3.5 models it provides to its users."
"We have many use cases for the solution, such as digitalizing records, a chatbot looking at records, and being able to use generative AI on them."
"The product is easy to integrate with our IT workflow."
"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."
"My preferred aspects are natural language processing and question-answering."
"The solution is easy to use compared to other frameworks like PyTorch and TensorFlow."
"It is stable."
"There are numerous libraries available, and the documentation is rich and step-by-step, helping us understand which model to use in particular conditions."
"The product is reliable."
"I like that Hugging Face is versatile in the way it has been developed."
"The tool's most valuable feature is that it's open-source and has hundreds of packages already available. This makes it quite helpful for creating our LLMs."
 

Cons

"The solution needs to accommodate smaller companies."
"The solution's response is a bit slow sometimes."
"Sometimes, the responses are repetitive."
"I faced one issue with Azure OpenAI: My customer wanted more clarity on the pricing. They were not able to get proper answers from the documentation or the pricing calculator. I suggest that Microsoft maintain standardization in the pricing details published in the documentation and the pricing calculator."
"One major drawback of Azure OpenAI is its availability, as it's not consistently accessible for effective use."
"Latency performance is a major part. And I'm seeking support for multiple models that handle text, images, videos, and voice. I'm from India, and I'm looking for more support in Indian languages. There are 18 official languages and many more unofficial. We need support for these languages, especially in voice moderation, which is not yet available."
"Sometimes, it gives answers in English, even when the request is in Polish."
"There is room for improvement in their support services."
"The solution must provide an efficient LLM."
"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."
"Regarding scalability, I'm finding the multi-GPU aspect of it challenging."
"Most people upload their pre-trained models on Hugging Face, but more details should be added about the models."
"It can incorporate AI into its services."
"Hugging Face could improve by implementing a search engine or chat bot feature similar to ChatGPT."
"Implementing a cloud system to showcase historical data would be beneficial."
"Initially, I faced issues with the solution's configuration."
 

Pricing and Cost Advice

"While the product meets our business requirements well, I consider it relatively expensive, especially for individual users like myself."
"I rate the product pricing six out of ten."
"The tool costs around 20 dollars a month."
"The cost is pretty high. Even by US standards, you would find it high."
"Cost-wise, the product's price is a bit on the higher side."
"The pricing is acceptable, and it's delivering good value for the results and outcomes we need."
"The solution's pricing depends on the services you will deploy."
"The cost structure depends on the volume of data processed and the computational resources required."
"So, it's requires expensive machines to open services or open LLM models."
"The solution is open source."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
13%
Manufacturing Company
11%
Government
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?
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.
What needs improvement with Azure OpenAI?
Maybe with the next release, the response will be more precise and more human-like.
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: March 2025.
845,040 professionals have used our research since 2012.