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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

"OpenAI integrates seamlessly with the broader Microsoft Azure ecosystem, and that provides synergies with the other solutions. This integration makes it much easier to build solutions."
"Azure OpenAI is useful for benchmarking products."
"Generative AI or GenAI seems to be the best part of the solution."
"Azure OpenAI is used as chat services, allowing me to replace human tasks with analytical capabilities."
"The most valuable feature is the ALM."
"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."
"Our clients are interested in building knowledge bases, particularly in child welfare. In this domain, we focus on supporting caseworkers by compiling and organizing relevant information. This information is then stored in a database using a query. The database generates summaries and reminders for specific actions and even facilitates sending emails to parents or other relevant parties. The system's complexity is tailored to the specific needs of child welfare cases. Additionally, we're exploring opportunities to assist a healthcare organization. Specifically, we're working on streamlining the process of filling out forms required for insurance claims. This effort aims to ensure that hospitals can receive funding or payment for the care they provide."
"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 like that Hugging Face is versatile in the way it has been developed."
"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."
"The solution is easy to use compared to other frameworks like PyTorch and TensorFlow."
"The product is reliable."
"It is stable."
"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."
"My preferred aspects are natural language processing and question-answering."
 

Cons

"One area for improvement is providing more flexibility in configuration and connectivity with external tools."
"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."
"Maybe with the next release, the response will be more precise and more human-like."
"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."
"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."
"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 product must improve its dashboards."
"Hugging Face could improve by implementing a search engine or chat bot feature similar to ChatGPT."
"The solution must provide an efficient LLM."
"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."
"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."
"Implementing a cloud system to showcase historical data would be beneficial."
"The initial setup can be rated as a seven out of ten due to occasional issues during model deployment, which might require adjustments."
"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."
 

Pricing and Cost Advice

"The solution's pricing is normal worldwide but expensive in Turkey because Turkey's currency is different."
"The pricing is acceptable, and it's delivering good value for the results and outcomes we need."
"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."
"The solution's pricing depends on the services you will deploy."
"We started with monthly payments, but we plan to switch to yearly billing once we've stabilized our solution."
"The licensing is interaction-based, meaning transactional. It's reasonably priced for now."
"If you consider the long-term aspect of any project, Azure OpenAI is a costly 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."
"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."
"So, it's requires expensive machines to open services or open LLM models."
"Hugging Face is an open-source solution."
"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%
Government
5%
Computer Software Company
10%
University
10%
Financial Services Firm
9%
Comms Service Provider
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.
869,771 professionals have used our research since 2012.