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Google Gemini Reviews

Vendor: Google
4.1 out of 5
Badge Ranked 1
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What is Google Gemini?

Google Gemini is a powerful new family of large language models (LLMs) designed to be multimodal, meaning they can understand and process different types of information like text, code, audio, images, and video. It builds upon the previous LaMDA and PaLM 2 models, offering significant advancements in capability and safety.

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Google Gemini mindshare

As of March 2025, the mindshare of Google Gemini in the Large Language Models (LLMs) category stands at 12.5%, down from 50.0% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Large Language Models (LLMs)
 
 
Key learnings from peers

Valuable Features

Google Gemini's multi-modal function, text writing capabilities for social media, and image generation stand out. Users benefit from the comprehensive Google ecosystem, smooth data extraction from PDFs, custom chatbot creation, and an experimental search module. Its integration with Google Workspace enhances internal file access, improving summarization, email creation, and document handling. Processing large data sets and supporting real-time conversations offer productivity gains, with continuous improvements being a noted advantage.
  • "The most valuable feature of Google Gemini is its ability to function as an intelligent assistant, providing accurate answers to natural language queries and performing translations."
  • "I would rate my overall experience with Google Gemini as a nine out of ten."
  • "Recently, Google Gemini has been very stable, without performance issues, even handling network problems smoothly with a retry."

Room for Improvement

Google Gemini requires enhancements in customization options, Canvas mode, and web search tools compared to ChatGPT. Additionally, it lacks model justification and interpretability, appearing as a black box. Export capabilities to Excel or Google Sheets and support for PowerPoint or Google Slides are currently unavailable. Accuracy in answers and context retention in lengthy documents need improvement. Increasing the context token limit would help when handling substantial documents.
  • "The binning process could be more intuitive, especially when grouping data into categories like age groups."
  • "Sometimes Google Gemini could hallucinate and provide incorrect information, which needs explanation for correction."
  • "Google Gemini needs more accurate answers and the ability to export data to Excel or Google Sheets."

Pricing

Google Gemini users find its pricing to be generally reasonable, offering competitive pricing compared to other solutions. However, they report that setup costs are high, and the need for multiple licenses can increase expenses significantly. Though the per license cost is similar to competitors, currency fluctuations can challenge ongoing subscription affordability. With trial purposes, the pricing is deemed reasonable but might become more costly depending on license quantities.

Popular Use Cases

Organizations primarily employ Google Gemini for AI-driven tasks, utilizing its capabilities in general conversation, multi-modal functions, and large language models. They leverage it for financial services, marketing, and accessing, revising, and summarizing internal documents. Entities also utilize it for creating emails, organizing documents, data extraction, summarizing large datasets, and analysis. Google Gemini supports federated models to aggregate different large language models, enabling businesses to streamline processes and serve clients effectively.

Service and Support

Google Gemini customer service receives mixed feedback. Some users haven't interacted with support yet rate it highly. Others find the general Google support excellent due to rapid response and an active community. However, some describe it as difficult to reach, giving it an average rating.

Deployment

Google Gemini's initial setup is regarded as straightforward and consistent with well-structured Google flows. While Google Cloud environments can appear complicated, users did not encounter significant issues. Some noted the ease of activation with no installation needed, only the subscription activation. Users found the setup comparable to other Google services, and many did not face any challenges, indicating a smooth experience.

Scalability

Google Gemini is rated for its strong scalability due to its robust infrastructure. Users give it varied scores, with some rating it exceptionally while others have minor reservations. It efficiently manages large files, including PDFs, although expenses are influenced by exchange rates.

Stability

Users report that Google Gemini is notably stable, with ratings of eight or ten out of ten. It handles network issues and retries effectively, showcasing excellent data storage and compute capabilities. Although it exhibits occasional hallucinations, particularly common among AI systems, recent feedback indicates improved stability without performance problems.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
Download our Google Gemini Buyer's Guide for additional reliable information.

Top industries

By visitors reading reviews
University
13%
Computer Software Company
10%
Government
7%
Comms Service Provider
7%
Educational Organization
7%
Healthcare Company
5%
Financial Services Firm
5%
Non Profit
4%
Manufacturing Company
4%
Real Estate/Law Firm
4%
Retailer
4%
Media Company
4%
Construction Company
4%
Outsourcing Company
3%
Insurance Company
3%
Recreational Facilities/Services Company
2%
Performing Arts
2%
Legal Firm
1%
Hospitality Company
1%
Wholesaler/Distributor
1%
Maritime Company
1%
Energy/Utilities Company
1%
Pharma/Biotech Company
1%
Agriculture
1%
Consumer Goods Company
1%
Aerospace/Defense Firm
1%
Logistics Company
1%
Transportation Company
1%

Learn more about Google Gemini

Released in December 2023, Gemini comes in three versions: Ultra, Pro, and Nano. Ultra is the most powerful, tackling complex tasks, while Pro excels at scaling across various situations. Nano, the most efficient, runs directly on devices.

Key features include:

  • Multimodality: Seamlessly integrates and understands diverse information types.
  • Efficiency: Employs a "Mixture-of-Experts" architecture for resource optimization.
  • Safety: Underwent rigorous evaluations for bias, toxicity, and potential risks.
  • Accessibility: Available in different sizes to suit various needs and applications.

Google Gemini was previously known as Google Bard.

Related questions

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