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Azure OpenAI vs Hugging Face comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 27, 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
6.6
Number of Reviews
34
Ranking in other categories
No ranking in other categories
Hugging Face
Ranking in AI Development Platforms
3rd
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 October 2025, in the AI Development Platforms category, the mindshare of Azure OpenAI is 9.4%, down from 18.1% compared to the previous year. The mindshare of Hugging Face is 11.4%, up from 11.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Market Share Distribution
ProductMarket Share (%)
Azure OpenAI9.4%
Hugging Face11.4%
Other79.2%
AI Development Platforms
 

Featured Reviews

Rafael Keller - PeerSpot reviewer
Creates effective scheduling agents with responsive AI capabilities
I am using it to create agents to schedule appointments for clinics and professionals in general. It serves both small and major companies. The primary use case involves creating agents Its ability to understand and respond well to queries, including language translation for clients, is…
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 product's initial setup phase was pretty easy."
"GPT was useful for our projects."
"The product is easy to integrate with our IT workflow."
"It is easy to integrate and develop a solution. Most customers are concerned about the security of their data and how cost-effective it is. We have developed some methodologies so that our customers will not be charged too much for these OpenAI services but will still get the same kind of performance and results. It's all developed on Azure, so customers also see its benefit."
"Its versatility makes it incredibly useful for technical problem-solving, content creation, data analytics, and more."
"Azure OpenAI is useful for benchmarking products."
"Generative AI or GenAI seems to be the best part of the solution."
"The most valuable features include analyzing comments and preparing requests for customers, making emails easier and faster."
"It is stable."
"I would rate this product nine out of ten."
"The product is reliable."
"Hugging Face provides open-source models, making it the best open-source and reliable solution."
"Overall, the platform is excellent."
"The most valuable features are the inference APIs as it takes me a long time to run inferences on my local machine."
"My preferred aspects are natural language processing and question-answering."
"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."
 

Cons

"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 accuracy in these languages requires improvement."
"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 product must improve its dashboards."
"The solution's response is a bit slow sometimes."
"The UI could be a little easier."
"One area for improvement is providing more flexibility in configuration and connectivity with external tools."
"The solution needs to accommodate smaller companies."
"One major drawback of Azure OpenAI is its availability, as it's not consistently accessible for effective use."
"Regarding scalability, I'm finding the multi-GPU aspect of it challenging."
"Hugging Face could improve by implementing a search engine or chat bot feature similar to ChatGPT."
"Initially, I faced issues with the solution's configuration."
"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."
"The initial setup can be rated as a seven out of ten due to occasional issues during model deployment, which might require adjustments."
"Most people upload their pre-trained models on Hugging Face, but more details should be added about the models."
"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."
"Access to the models and datasets could be improved."
 

Pricing and Cost Advice

"The platform offers a flexible pricing model which depends on the features and capabilities we utilize."
"The tool costs around 20 dollars a month."
"The cost is quite high and fixed."
"According to the negotiations taking place and the contract, there is a need to make either monthly or yearly payments to use the solution."
"If you consider the long-term aspect of any project, Azure OpenAI is a costly solution."
"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."
"It's a token-based system, so you pay per token used by the model."
"Hugging Face is an open-source solution."
"I recall seeing a fee of nine dollars, and there's also an enterprise option priced at twenty dollars per month."
"We do not have to pay for the product."
"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."
"So, it's requires expensive machines to open services or open LLM models."
"The solution is open source."
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Top Industries

By visitors reading reviews
Computer Software Company
13%
Financial Services Firm
12%
Manufacturing Company
10%
Educational Organization
5%
Computer Software Company
10%
University
9%
Comms Service Provider
9%
Financial Services Firm
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business15
Midsize Enterprise1
Large Enterprise18
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise2
Large Enterprise3
 

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 terms of pricing for Azure OpenAI, I would rate it as average compared to Gemini. Currently, Gemini is becoming increasingly popular, which prompts leadership to consider a switch primarily due ...
What needs improvement with Azure OpenAI?
While it is good, we sometimes encounter hallucination issues, which is a significant concern. We are changing the prompt and fine-tuning it, but we still face some inconsistent behavior. We have s...
What do you like most about Hugging Face?
My preferred aspects are natural language processing and question-answering.
What needs improvement with Hugging Face?
It is challenging to suggest specific improvements for Hugging Face, as their platform is already very well-organized and efficient. However, they could focus on cleaning up outdated models if they...
What is your primary use case for Hugging Face?
I am working on AI with various large language models for different purposes such as medicine and law, where they are fine-tuned with specific requirements. I download LLMs from Hugging Face for th...
 

Overview

Find out what your peers are saying about Azure OpenAI vs. Hugging Face and other solutions. Updated: September 2025.
869,513 professionals have used our research since 2012.