Azure OpenAI Service vs. Vertex AI

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure OpenAI Service
Score 7.5 out of 10
N/A
Azure OpenAI Service, a service from Microsoft's Azure suite available in preview, includes pre-generated AI models that enable users to apply advanced coding and language models to a variety of use cases, enabling new reasoning and comprehension capabilities for building applications. Users can apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data.N/A
Vertex AI
Score 8.6 out of 10
N/A
Vertex AI on Google Cloud is an MLOps solution, used to build, deploy, and scale machine learning (ML) models with fully managed ML tools for any use case.
$0
Starting at
Pricing
Azure OpenAI ServiceVertex AI
Editions & Modules
No answers on this topic
Imagen model for image generation
$0.0001
Starting at
Text, chat, and code generation
$0.0001
per 1,000 characters
Text data upload, training, deployment, prediction
$0.05
per hour
Video data training and prediction
$0.462
per node hour
Image data training, deployment, and prediction
$1.375
per node hour
Offerings
Pricing Offerings
Azure OpenAI ServiceVertex AI
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeOptional
Additional DetailsPricing is based on the Vertex AI tools and services, storage, compute, and Google Cloud resources used.
More Pricing Information
Community Pulse
Azure OpenAI ServiceVertex AI
Considered Both Products
Azure OpenAI Service

No answer on this topic

Vertex AI
Chose Vertex AI
Let's say that Azure OpenAI Service offers you exactly what you look for in simple-to-understand terms: your own private instance of OpenAI API backend.

Best Alternatives
Azure OpenAI ServiceVertex AI
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Google Cloud AI
Google Cloud AI
Score 8.4 out of 10
Medium-sized Companies
Posit
Posit
Score 9.1 out of 10
Google Cloud AI
Google Cloud AI
Score 8.4 out of 10
Enterprises
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Dataiku
Dataiku
Score 8.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure OpenAI ServiceVertex AI
Likelihood to Recommend
5.0
(1 ratings)
8.1
(7 ratings)
Performance
-
(0 ratings)
8.1
(3 ratings)
Configurability
-
(0 ratings)
8.6
(4 ratings)
User Testimonials
Azure OpenAI ServiceVertex AI
Likelihood to Recommend
Microsoft
The pricing doesn't seem fair to me if we compare the limitations and errors in the models. Also, they are currently working on new unified portal for all AI projects which is in beta preview. So, I guess we should wait until it matures, and fixes all the issues and should use once pricing and performance improves.
Read full review
Google
We needed to build some ML models and Vertex AI is one such place where all the functionalities are consolidated for model deployment, tweaking and monitoring. And although it is costly, it is compatible with google cloud services and is scalable which makes it the perfect tool for us.
Read full review
Pros
Microsoft
  • It's generative AI like ChatGPT but you get advanced models, so it's more powerful.
  • You can use API to automate the process of Generative AI tasks.
  • It also provides a sample script code on how we can use the API.
Read full review
Google
  • Vertex AI comes with support for LOTs of LLMs out of the box
  • MLOps tools are available that help to standardize operational aspects
  • Document AI is an out of the box feature that works just perfectly for our use cases of automating lots to tedious data extraction tasks from images as well as papers
Read full review
Cons
Microsoft
  • The user interface is similar to the Azure, so it's bit laggy, they should improve it.
  • The chat models sometimes return nothing, I guess they are still testing them.
  • The models we use have quota limitation on tokens and number of requests.
Read full review
Google
  • Customization of AutoML models - A must needed capability to be able to tweak hyperparameters and also working with different models
  • Model Explainability -Providing more comprehensive explanations about how models are utilizing features could be very beneficial
  • Model versioning and experiments tracking - Enhancing the versioning capability could be good for end users
Read full review
Performance
Microsoft
No answers on this topic
Google
Vertex AI is very user friendly and it is very fast. We can spin up instances pretty quickly and it allows to work with GPU instances without much planning. Pages load up very quickly and tasks are competed pretty much in time frame. It integrates with other systems also very well.
Read full review
Alternatives Considered
Microsoft
Overall, Azure OpenAI services are not worth using, but only reason I used it because I got it under Startup sponsorship from Microsoft. Pricing is very high.
Read full review
Google
Vertex AI is much more accessible to non-developers than IBM's product. Moreover, Vertex AI integrates well with other Google products, enhancing its capabilities. A big plus is its integration with cloud storage, that allows for better management and access of data. In all honesty, it wasn't much of a difficult choice to choose Vertex AI.
Read full review
Return on Investment
Microsoft
  • Honestly, I just started using it a few months ago, and I haven't seen any major benefits.
  • It has almost similar capabilities as free version of ChatGPT, so it's worth paying for chat models unless we need to use API.
  • ROI has not been impacted at all, as I mostly use free version over this to avoid higher charges.
Read full review
Google
  • It consolidated all the functionalities in one place for AI and ML development.
  • Scalable and compatible with google cloud services.
  • Though we can manually allocate resources, it is still very costly.
Read full review
ScreenShots

Vertex AI Screenshots

Screenshot of an introduction to generative AI on Vertex AI - Vertex AI Studio offers a Google Cloud console tool for rapidly prototyping and testing generative AI models.Screenshot of gen AI for summarization, classification, and extraction - Text prompts can be created to handle any number of tasks with Vertex AI’s generative AI support. Some of the most common tasks are classification, summarization, and extraction. Vertex AI’s PaLM API for text can be used to design prompts with flexibility in terms of their structure and format.Screenshot of Custom ML training overview and documentation - An overview of the custom training workflow in Vertex AI, the benefits of custom training, and the various training options that are available. This page also details every step involved in the ML training workflow from preparing data to predictions.Screenshot of ML model training and creation -  A guide that shows how Vertex AI’s AutoML is used to create and train custom machine learning models with minimal effort and machine learning expertise.Screenshot of deployment for batch or online predictions - When using a model to solve a real-world problem, the Vertex AI prediction service can be used for batch and online predictions.