Try our new research platform with insights from 80,000+ expert users

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 most valuable feature of Azure OpenAI stems from the GPT-3.5 models it provides to its users."
"Azure OpenAI has significantly reduced costs and increased efficiency in tasks such as aggressive testing of systems to avoid anomalies and trust issues."
"The most valuable feature is the ALM."
"Azure OpenAI is used as chat services, allowing me to replace human tasks with analytical capabilities."
"The most valuable features include analyzing comments and preparing requests for customers, making emails easier and faster."
"Azure OpenAI is very easy to use instead of AWS services."
"The solution has a very drag-and-drop environment. Instead of coding something from scratch or understanding any concept in extensive depth before deployment, this is good. Plus, they have an auto dataset, which means you can choose any dataset they have instead of providing your own. So that's also pretty nice."
"The product is easy to integrate with our IT workflow."
"Overall, the platform is excellent."
"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."
"The most valuable features are the inference APIs as it takes me a long time to run inferences on my local machine."
"There are numerous libraries available, and the documentation is rich and step-by-step, helping us understand which model to use in particular conditions."
"I like that Hugging Face is versatile in the way it has been developed."
"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."
"The solution is easy to use compared to other frameworks like PyTorch and TensorFlow."
 

Cons

"I have found the tool unreliable in certain use cases. I aim to enhance the system's latency, particularly in responding to calls. Occasionally, calls don't respond, so I want to improve reliability."
"The solution's response is a bit slow sometimes."
"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."
"Maybe with the next release, the response will be more precise and more human-like."
"There is room for improvement in their support services."
"Sometimes, the responses are repetitive."
"The dialogue manager needs to be improved."
"We are awaiting the new updates like multi-model capabilities."
"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."
"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."
"It can incorporate AI into its services."
"Hugging Face could improve by implementing a search engine or chat bot feature similar to ChatGPT."
"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."
"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."
"Implementing a cloud system to showcase historical data would be beneficial."
 

Pricing and Cost Advice

"The solution's pricing depends on the services you will deploy."
"The platform offers a flexible pricing model which depends on the features and capabilities we utilize."
"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 cost is pretty high. Even by US standards, you would find it high."
"If you consider the long-term aspect of any project, Azure OpenAI is a costly solution."
"Azure OpenAI is a bit more expensive than other services."
"While the product meets our business requirements well, I consider it relatively expensive, especially for individual users like myself."
"Hugging Face is an open-source solution."
"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."
"The solution is open source."
"So, it's requires expensive machines to open services or open LLM models."
report
Use our free recommendation engine to learn which AI Development Platforms solutions are best for your needs.
868,706 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Computer Software Company
14%
Financial Services Firm
12%
Manufacturing Company
10%
Government
5%
Computer Software Company
10%
University
10%
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.
868,706 professionals have used our research since 2012.