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Cerebras Fast Inference Cloud vs Google Gemini 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

Cerebras Fast Inference Cloud
Ranking in Large Language Models (LLMs)
9th
Average Rating
10.0
Reviews Sentiment
1.9
Number of Reviews
3
Ranking in other categories
No ranking in other categories
Google Gemini AI
Ranking in Large Language Models (LLMs)
1st
Average Rating
7.8
Reviews Sentiment
6.0
Number of Reviews
16
Ranking in other categories
AI Writing Tools (1st), AI Code Assistants (3rd), AI Proofreading Tools (1st)
 

Featured Reviews

reviewer2787606 - PeerSpot reviewer
Co-founder at a tech services company with 1-10 employees
Fast inference has enabled ultra-low-latency coding agents and continues to improve
I use the product for the fastest LLM inference for LLama 3.1 70B and GLM 4.6 We use it to speed up our coding agent on specific tasks. For anything that is latency-sensitive, having a fast model helps. The valuable features of the product are its inference speed and latency. There is room for…
Luís Silva - PeerSpot reviewer
Chief Technical Lead at a consultancy with 201-500 employees
Tool proves competitive with cost-effectiveness and speed while benefiting decision-making and integration capabilities, but shows room for enhancing creativity and handling large data contextually
There is another benefit in that Google Gemini is highly competitive from a cost perspective. The cost per token is very competitive. It's not the best - the Chinese models such as DeepSeek are better, but I can't use them. From a cost perspective, between European and United States options, Google Gemini is very competitive. It's not only its cost, it's also very performing. The time it takes to process the prompts and context information is very fast. It's one of the fastest models in the market. That's another advantage. There are other models which are also very good in quality but not as fast, such as Anthropic Claude. Google Gemini currently has a very good balance. The AI capabilities of Google Gemini are a multi-modal LLM which allows me to pass documents, images, and texts in the same prompt. Being multi-modal makes my life easier. I don't have to translate information before I can work with it. Google provides free tools to test scenarios, which speeds up development and reduces costs. It's a very fast and accurate model with quality responses.

Quotes from Members

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

Pros

"I recommend using it for speed and having a good fallback plan in case there are issues, but that's easy to do."
"Cerebras' token speed rates are unmatched, which can enable us to provide much faster customer experiences."
"The throughput increase has extended decision-making time by over 50 times compared to previous pipelines when accounting for burst parallelism."
"Google provides an out-of-the-box solution with a comprehensive ecosystem of tools."
"The integration of Gemini with other Google services is quite good; we develop the application using open source platforms such as LangGraph or LangChain, where the integration for Gemini is quite good."
"The most valuable feature of Google Gemini for us is its text writing capabilities, which we are using for writing texts and social media posts for our company's social media page."
"Recently, Google Gemini has been very stable, without performance issues, even handling network problems smoothly with a retry."
"Google Gemini AI is better in terms of searching the web, considering that Google Gemini AI is a property of Google, and the search results when looking for answers from the web are superior compared to those given by Alexa."
"I have compared responses from Gemini and ChatGPT and received similar results but presented differently, and every tool has its uniqueness; it is good, and I am enjoying using both tools, but most often I use ChatGPT because I haven't used Gemini recently."
"I would rate my overall experience with Google Gemini as a nine out of ten."
"It is like having an expert at my fingertips for those out-of-scope queries."
 

Cons

"There is room for improvement in the integration within AWS Bedrock."
"There is room for improvement in supporting more models and the ability to provide our own models on the chips as well."
"The binning process could be more intuitive, especially when grouping data into categories like age groups."
"I do not have a special recommendation for improvement."
"Google can improve in model justification and interpretability of answers."
"Google Gemini's biggest strength is also its drawback; it's excellent for generating reports and working with data in real-time, but it isn't the most creative LLM for tasks such as creating a digital storytelling campaign or crafting marketing messages."
"Google Gemini could improve its functionalities compared to other tools like ChatGPT, especially in the customization options, Canvas mode, and web search tools, which aren't as advanced."
"Google Gemini needs more accurate answers and the ability to export data to Excel or Google Sheets."
"Currently, it operates mostly autonomously, and while it provides structured activities, making the research configuration more accessible and flexible would be beneficial."
"When I have reached out to Google Support, it's been very limiting. I would rate Google at about a five."
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Top Industries

By visitors reading reviews
No data available
University
11%
Computer Software Company
9%
Comms Service Provider
8%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise6
Large Enterprise6
 

Questions from the Community

What is your experience regarding pricing and costs for Cerebras Fast Inference Cloud?
They are more expensive, but if you need speed, then it is the only option right now.
What is your primary use case for Cerebras Fast Inference Cloud?
I use the product for the fastest LLM inference for LLama 3.1 70B and GLM 4.6.
What advice do you have for others considering Cerebras Fast Inference Cloud?
Their support has been helpful, and I've had a few outages with them in the past, but they were resolved quickly. I recommend using it for speed and having a good fallback plan in case there are is...
What is your experience regarding pricing and costs for Google Gemini?
The pricing of Google Gemini AI is not well understood, so no feedback can be provided on the cost. It was thought to have come together with the device subscription.
What needs improvement with Google Gemini?
Google Gemini AI is not used much because it does not appear to be as responsive or as effective as Alexa when responding to questions, queries, instructions, or commands. When in a room with Googl...
What is your primary use case for Google Gemini?
Google Gemini AI is used for common, basic digital assistant queries such as asking about the weather and the time. Often there are conflicting responses from Google Home, Google Home Mini, and the...
 

Comparisons

No data available
 

Also Known As

No data available
Google Bard
 

Overview

Find out what your peers are saying about Cerebras Fast Inference Cloud vs. Google Gemini AI and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.