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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
6.5
Number of Reviews
35
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

"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."
"The AI search functionality is particularly effective, as it creates summaries from data."
"It's very easy to set up and easy to use; there is no issue with that."
"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."
"I would rate it a nine out of ten."
"It's very easy to set up and easy to use; there is no issue with that."
"You just have to write accurate prompts according to your requirements, and the solution gives very good results."
"The product's initial setup phase was pretty easy."
"I like that Hugging Face is versatile in the way it has been developed."
"I would rate this product nine out of ten."
"The product is reliable."
"The solution is easy to use compared to other frameworks like PyTorch and TensorFlow."
"Hugging Face provides open-source models, making it the best open-source and reliable solution."
"My preferred aspects are natural language processing and question-answering."
"I appreciate the versatility and the fact that it has generalized many models."
"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

"There is room for improvement in their support services."
"Since we don't train the model on our data, it's a struggle to ensure OpenAI answers questions exclusively from our data. During user testing, we found ways to make the system provide answers from outside sources."
"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."
"There are no available updates of information that are currently provided."
"Sometimes, the responses are repetitive."
"The main issue with Azure OpenAI is the inconsistency in output. We have a set template instruction, and it should generate within those parameters without any creativity because it's meant for regulatory authoring documents."
"We encountered challenges related to question understanding."
"One area for improvement is providing more flexibility in configuration and connectivity with external tools."
"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."
"It can incorporate AI into its services."
"Most people upload their pre-trained models on Hugging Face, but more details should be added about the models."
"The solution must provide an efficient LLM."
"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."
"I believe Hugging Face has some room for improvement. There are some security issues. They provide code, but API tokens aren't indicated. Also, the documentation for particular models could use more explanation. But I think these things are improving daily. The main change I'd like to see is making the deployment of inference endpoints more customizable for users."
"Access to the models and datasets could be improved."
 

Pricing and Cost Advice

"Azure OpenAI is a bit more expensive than other services."
"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 pretty high. Even by US standards, you would find it high."
"According to the negotiations taking place and the contract, there is a need to make either monthly or yearly payments to use the solution."
"The cost structure depends on the volume of data processed and the computational resources required."
"The solution's pricing is normal worldwide but expensive in Turkey because Turkey's currency is different."
"The licensing is interaction-based, meaning transactional. It's reasonably priced for now."
"The platform offers a flexible pricing model which depends on the features and capabilities we utilize."
"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."
"The solution is open source."
"Hugging Face is an open-source solution."
"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."
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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%
Financial Services Firm
9%
Comms Service Provider
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business16
Midsize Enterprise1
Large Enterprise19
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.
872,655 professionals have used our research since 2012.