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Cohere vs Google Vertex AI comparison

 

Comparison Buyer's Guide

Executive Summary

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

Cohere
Ranking in AI Development Platforms
19th
Average Rating
7.4
Reviews Sentiment
6.6
Number of Reviews
3
Ranking in other categories
AI Writing Tools (9th), Large Language Models (LLMs) (6th), AI Proofreading Tools (8th)
Google Vertex AI
Ranking in AI Development Platforms
2nd
Average Rating
8.2
Reviews Sentiment
6.4
Number of Reviews
14
Ranking in other categories
AI-Agent Builders (4th)
 

Mindshare comparison

As of October 2025, in the AI Development Platforms category, the mindshare of Cohere is 1.1%, up from 0.1% compared to the previous year. The mindshare of Google Vertex AI is 10.3%, down from 19.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Market Share Distribution
ProductMarket Share (%)
Google Vertex AI10.3%
Cohere1.1%
Other88.6%
AI Development Platforms
 

Featured Reviews

Gokul Anil - PeerSpot reviewer
Has streamlined test creation and analysis while needing better semantic accuracy for specific domain knowledge
Cohere is very useful because I have been in scenarios where code was written with multiple reusable concepts containing many functionalities covered as different functions, but without descriptions of what particular functions were doing. We used Cohere intelligence and its knowledge on Oracle ERP PPM, and it was able to read through all the TypeScript code and create descriptions intelligently, which were almost 90% correct when reviewed. It was very useful because we had 500-plus reusables, and it was able to analyze all of them and put them into a catalog. This makes it very easy to find and use the catalog to determine whether existing functionality is already implemented, preventing redundant implementations. When it creates a new test, it creates it almost 70 to 80% correctly without errors. The time savings are significant - what previously took one or two days can now be completed in two to three hours maximum. We can complete many more tests in a day or sprint with Cohere's help. Along with test automation, we handle analysis tasks, and now we have more time for better analysis. We are planning to implement test analysis capabilities as well. Once you receive the requirements and test cases, you can directly use them as input, and it will generate all artifacts and test data.
Hamada Farag - PeerSpot reviewer
Customization and integration empower diverse AI applications
We are familiar with most Google Cloud services, particularly infrastructure services, storage, compute, AI tools, containerization, GCP containerization, and cloud SQL. We are familiar with approximately eighty percent of Google's services, primarily related to infrastructure, AI, containers, backup, storage, and compute. We are familiar with Gemini AI and Google Vertex AI, and we have completed some exercises and cases with our customers for Google AI. We use automation in machine learning. I work with a team where everyone has specific responsibilities. We have design and development processes in place. Based on my experience, I would rate Google Vertex AI a 9 out of 10.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"When it creates a new test, it creates it almost 70 to 80% correctly without errors; the time savings are significant—what previously took one or two days can now be completed in two to three hours maximum."
"A key advantage of integrating Cohere’s reranking model is that it aligns with client requests to include a reranking module — a widely recognized method for improving RAG quality. Additionally, the API demonstrates strong performance in terms of response speed."
"The very first thing that I really like about it is the support team. They're really available on Discord, and they answer all of your questions."
"The support is perfect and fantastic."
"Vertex comes with inbuilt integration with GCP for data storage."
"Vertex AI possesses multiple libraries, so it eliminates the need for extensive coding."
"The monitoring feature is a true life-saver for data scientists. I give it a ten out of ten."
"Google Vertex AI is an out-of-the-box and very easy-to-use solution."
"The most valuable feature we've found is the model garden, which allows us to deploy and use various models through the provided endpoints easily."
"Google Vertex AI is better for deployment, configuration, delivery, licensing, and integration compared to other AI platforms."
"The most valuable features of the solution are that it is quite flexible, and some of the services are almost low-code, with no-code services, so it gives agents flexibility to build the use cases according to the operational needs."
 

Cons

"Cohere has text generation. I think it is mainly focused on AI search. If there was a way to combine the searches with images, I think it would be nice to include that."
"When performing similarity matching between text descriptions and the catalog descriptions created using Cohere, the matching could be improved."
"It's challenging for us to make a conclusion about quality enhancement by using reranking models, as solid evaluation methodology for reranking is still immature."
"It takes a considerable amount of time to process, and I understand the technology behind why it takes this long, but this is something that could be reduced."
"Google can improve Google Vertex AI in terms of analysis and accuracy. When passing a very large context, instead of receiving vague responses, it would be better if the system could prompt users not to pass overly large prompts and provide clearer guidance on how to fine-tune Gemini for specific use cases."
"The solution is stable, but it is quite slow. Maybe my data is too large, but I think that Google could improve Vertex AI's training time."
"We used AutoML feature for developing AI models automatically, but we are not comfortable with the performance of those models."
"It is not completely mature and needs some features and functions. The interface needs to be more user-friendly."
"It would be beneficial to have certain features included in the future, such as image generators and text-to-speech solutions."
"I think the technical documentation is not readily available in the tool."
"I believe that Vertex AI is a robust platform, but its effectiveness depends significantly on the domain knowledge of the developer using it. While Vertex AI does offer support through the console UI in the Google Cloud environment, it is better suited for technical members who have a deeper understanding of machine learning concepts. The platform may be challenging for business process developers (BPDUs) who lack extensive technical knowledge, as it involves intricate customization and handling numerous parameters. Effectively utilizing Vertex AI requires not only familiarity with machine learning frameworks like TensorFlow or PyTorch but also a proficiency in Python programming. The complexity of these requirements might pose challenges for less technically oriented users, making it crucial to have a solid foundation in both machine learning principles and Python coding to extract the full value from Vertex AI. It would be beneficial to have a streamlined process where we can leverage the capabilities of Vertex AI directly through the BigQuery UI. This could involve functionalities such as creating machine learning models within the BigQuery UI, providing a more user-friendly and integrated experience. This would allow users to access and analyze data from BigQuery while simultaneously utilizing Vertex AI to build machine learning models, fostering a more cohesive and efficient workflow."
 

Pricing and Cost Advice

Information not available
"The solution's pricing is moderate."
"I think almost every tool offers a decent discount. In terms of credits or other stuff, every cloud provider provides a good number of incentives to onboard new clients."
"The Versa AI offers attractive pricing. With this pricing structure, I can leverage various opportunities to bring value to my business. It's a positive aspect worth considering."
"The price structure is very clear"
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Top Industries

By visitors reading reviews
Manufacturing Company
12%
Computer Software Company
9%
Financial Services Firm
8%
Government
7%
Computer Software Company
14%
Financial Services Firm
10%
Manufacturing Company
9%
Educational Organization
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise3
Large Enterprise7
 

Questions from the Community

What is your experience regarding pricing and costs for Cohere?
I'm not in the position to answer that question because I was not the one who deployed that model, but I believe it is because we see the model name as ARN name, so it's most likely coming from Bed...
What needs improvement with Cohere?
It would be better to have a dashboard for users to showcase how reranking helps improve quality. When end users choose the service, they want to see the actual output. The evaluation part is chall...
What is your primary use case for Cohere?
We founded this company two and a half years ago, and since the middle of 2022, we foresaw the trending of generative AI and large language models, so my startup is working on developing generative...
What do you like most about Google Vertex AI?
We extensively utilize Google Cloud's Vertex AI platform for our machine learning workflows. Specifically, we leverage the IO branch for EDA data in Suresh Live Virtual, employing Forte IT for trai...
What is your experience regarding pricing and costs for Google Vertex AI?
They have different pricing models like pay-as-you-go or subscription model, and total cost of ownership. It is comparatively cheaper than Azure.
What needs improvement with Google Vertex AI?
We used AutoML feature for developing AI models automatically, but we are not comfortable with the performance of those models. We have to do some fine-tuning, hyperparameter optimization, and othe...
 

Overview

Find out what your peers are saying about Cohere vs. Google Vertex AI and other solutions. Updated: October 2025.
872,706 professionals have used our research since 2012.