Gemini is the latest iteration of Google’s AI technology. This solution has become a valuable tool for tackling modern business challenges. Use cases include marketing, data analysis, idea generation, report generation, etc.

This article dives into the detailed Google Gemini statistics. We will highlight its strengths and compare its features to those of other leading language models. Let’s explore the numbers to understand how this solution stands out in the AI competition.

 

Key Google Gemini Statistics

Below are the most notable Google Gemini stats:

  • Google Gemini recorded 313.9 million total visits in May 2024. Specifically, desktop visits reached 143.1 million, and mobile visits totaled 170.8 million.
  • Traffic peaked in March with 182.6 million desktop visits and 250.8 million mobile visits.
  • The United States led traffic sources at 19.66%. India follows at 9.18%, Brazil – at 4.38%, the United Kingdom – at 3.36%, and Colombia – at 3.32%.
  • The age group 25-34 years constituted the largest segment of users at 33.38%.
  • Google Gemini's user base is 58.34% male and 41.66% female.
  • 40% of users utilize Google Gemini for research purposes. 30% of respondents use it for creativity, 20% – for productivity, and 10% – for entertainment.
  • Among the most popular language models, Gemini 1.5 Flash is the fastest, with 141 tokens per second.
  • Gemini 1.5 Flash is priced at $0.8 per 1M tokens, making it a cost-effective option compared to other models.
  • Gemini 1.5 Pro has a context window of up to two million tokens, the longest of any large-scale foundation model.
  • The 1.5 Pro version performs best in code generation, math problem-solving, reasoning, and other capabilities among all Gemini models.

Google Gemini Overview

Let’s go over the key details of this language model launched by Google:

Attribute
Details

Google Gemini AI Release Date

Google Gemini: December 6, 2023
Bard (former version): March 21, 2023

Parent Company

Google, under Alphabet Inc.

Available Regions

Over 230 countries and territories

Language Support

Over 40 languages, including Chinese, Korean, Arabic, Hindi, and Spanish

Language Model

LaMDA (Language Models for Dialog Applications)

Model Variants

Gemini 1.0 Pro: For natural language tasks and code generation
Gemini 1.5 Pro: For complex reasoning tasks, e.g., code and text generation, text editing, problem-solving, etc.
Gemini 1.5 Flash: For fast and versatile performance across a diverse variety of tasks
Gemini 1.0 Ultra: For tackling highly complex tasks demanding a vast understanding of the world and intricate reasoning abilities
Gemini 1.0 Nano: For tasks that need to happen directly on a device, e.g., basic text processing or speech recognition

Training Dataset Size

Gemini Pro: Around 5.5 trillion tokens
Gemini Ultra: Estimated to be roughly double that of Pro. Thus, somewhere around 11 trillion tokens

Knowledge Cutoff

Early 2023; updates after this period may not be included

Websites Like Gemini

ChatGPT, Microsoft Bing AI, Claude

Source: Google AI for Developers, Google Blog

 

Now that we got to know what Google Gemini is, let’s dive into the usage stats.

Google Gemini Statistics: Usage Trends

Google Gemini attracts millions of users globally. Let’s review its performance in several key usage trends.

 

There were 143.1 million desktop visits and 170.8 million mobile visits in May 2024.

In February 2024, Google Gemini statistics showed 134.4 million visits on desktop and 181.7 million on mobile. Visits peaked in March with 182.6 million on desktop (a 35.84% increase) and 250.8 million on mobile (a 38.07% increase). However, traffic declined in the subsequent months. Specifically, there were 143.1 million desktop visits and 170.8 million mobile visits in May 2024.

Google Gemini statistics DOIT Staffing Monthly visits

In the Claude vs Google Gemini vs ChatGPT comparison, the latter dominates in total visits. From February to April 2024, ChatGPT had an impressive 5.202 billion total visits. It significantly outpaced Google Gemini’s 1.164 billion. Meanwhile, Claude recorded 141.2 million.

 

Google Gemini attracted 60.05 million unique visitors in April 2024.

In February 2024, the platform had 65.64 million unique visitors overall. There was a slight decline, with unique visitors dropping to 60.05 million by April. Gemini number of users on desktop started at 25.29 million and decreased slightly to 24.41 million. Meanwhile, mobile unique visitors dropped from 40.34 million to 35.64 million over the same period.

Google Gemini statistics DOIT Staffing Unique monthly visitors

 

The bounce rate on mobile increased to 34.27% in May 2024.

Google Gemini statistics by month show a relatively stable bounce rate with slight fluctuations. In February 2024, the desktop bounce rate was 26.50%. The value increased slightly to 29.35% by May. The mobile indicator saw a minor increase from 32.25% in February to 34.27% in May.

Month
Desktop
Change
Mobile
Change

February 24

26.50%

–

32.25%

–

March 24

29.09%

+9.77%

32.49%

+0.74%

April 24

29.44%

+1.20%

33.81%

+4.06%

May 24

29.35%

-0.31%

34.27%

+1.36%

 

There is an average of 5.11 pages per visit on mobile in May 2024.

Engagement on Google Gemini is evident through the pages per visit metric. Desktop users visited an average of 3.3 pages per session in February, maintaining this level in May. Mobile users averaged 5.01 pages per visit in February, ending at 5.11 pages per visit in May.

Month
Desktop
Change
Mobile
Change

February 24

3.3

–

5.01

–

March 24

3.19

-3.28%

5.22

+4.13%

April 24

3.22

+0.80%

4.94

-5.33%

May 24

3.3

+2.36%

5.11

+3.40%

 

The average visit duration on mobile was 8 minutes and 1 second in May 2024.

The average visit duration for desktop users was 4 minutes and 16 seconds in February. It slightly increased to 4 minutes and 22 seconds by May. Mobile users had a more extended visit duration. Specifically, it started at 7 minutes and 55 seconds. There were minor fluctuations in May, ending at 8 minutes and 1 second.

Month
Desktop
Change
Mobile
Change

February 24

0:04:16

–

0:07:55

–

March 24

0:04:13

-0.91%

0:08:29

+7.22%

April 24

0:04:14

+0.14%

0:08:01

-5.43%

May 24

0:04:22

+3.35%

0:08:01

–

 

Google Gemini is a leader in user engagement compared to ChatGPT and Claude.

According to the latest Google Gemini statistics, the platform records 4.28 pages per visit on average. In contrast, ChatGPT has 3.94 pages per visit, while Claude trails with 3.45 pages per visit. Thus, we can conclude that Google’s model has higher user engagement and interaction per session.

However, ChatGPT leads in other metrics, such as monthly visits, with 1.734 billion compared to Google Gemini’s 388.0 million and Claude’s 47.07 million.

Metric
Google Gemini
ChatGPT
Claude

Monthly visits

388.0M

1.734B

47.07M

Monthly unique visitors

62.60M

208.8M

7.855M

Visits / Unique visitors

6.2

8.31

5.99

Visit duration

0:06:30

0:07:52

0:05:34

Pages per visit

4.28

3.94

3.45

Bounce rate

31.03%

31.42%

39.21%

Page views

1.662B

6.836B

162.4M

 

Google Gemini leads in mobile usage compared to ChatGPT and Claude.

Google Gemini statistics show the model’s strong presence in mobile app usage. Specifically, 57.40% of its user base is on mobile devices. In contrast, ChatGPT has a higher desktop usage at 62.40%, while only 37.60% of its users are on mobile. Similarly, Claude has 73.80% of its users on desktop and only 26.20% on mobile.

Google Gemini statistics DOIT Staffing Device distribution Gemini vs ChatGPT vs Claude

 

40% of users utilize Google Gemini for research purposes.

Additionally, 30% of the respondents reported using this language model for creative endeavors. Some use cases include writing poems, scripts, and stories.

Furthermore, 20% indicated that they use Google Gemini for productivity. The examples encompass work or school projects. The remaining 10% of users engage with this language model for entertainment. For instance, they use it to play games and search for videos and music.

Google Gemini statistics DOIT Staffing use purposes

 

Source: SimilarWeb, My Learning

Traffic Location, Demographics, and Sources

Google Gemini’s traffic distribution shows significant engagement. It spans across various regions, age groups, and marketing channels.

 

The United States was the top traffic source for Google Gemini in April 2024.

As of April 2024, the United States led the traffic sources for Google Gemini with 19.66%. India followed with 9.18%, Brazil – with 4.38%, the United Kingdom – 3.36%, and Colombia – 3.32%. The rest of the world contributed 60.1% of the traffic.

Google Gemini statistics DOIT Staffing top 5 traffic sources

 

The largest age group of Google Gemini users is 25-34. It makes up 33.38% of the audience.

Google Gemini statistics highlight that the 25-34 age group is the most significant demographic. It comprises 33.38% of the audience. The 18-24 age group follows with 25.5%, while the 35-44 group accounts for 19.04%. Smaller segments include the 45-54 group at 11.95%, the 55-64 group at 6.34%, and users aged 65 and above at 3.79%.

Google Gemini statistics DOIT Staffing age distribution

 

Male users represent 58.34% of Google Gemini’s audience.

Gender distribution data indicates that male users dominate the platform. This segment made up 58.34% of the audience. Meanwhile, the female counterparts constitute 41.66%.

Google Gemini statistics DOIT Staffing gender distribution

 

Direct traffic to Google Gemini peaked at 292.2 million in March 2024.

Direct traffic peaked at 292.2 million in March 2024, up from 209 million in February. Although there was a slight decline to 283.7 million in April, the Google Gemini statistics showed a 35.74% increase from February. Social media traffic also experienced a rise, with a 36.87% increase from February to April. Organic search traffic grew by 26.79%, while email traffic showed a modest increase of 1.46%. Conversely, referral traffic decreased by 15.61% over the same period.

Channels
February
March
April
Change (April vs February)

Direct

209M

292.2M

283.7M

+35.74%

Email

93.81K

163.98K

128.16K

+1.46%

Referrals

11.4M

10.84M

9.62M

-15.61%

Social

5.94M

9.25M

8.13M

+36.87%

Organic Search

81.79M

111.0M

103.7M

+26.79%

Paid Search

7.80M

9.75M

8.95M

+14.74%

Display Ads

22.96K

43.44K

32.20K

+40.24%

Source: SimilarWeb

Google Gemini Cost

Let’s explore Google Gemini’s cost structure and compare it with other language models.

 

Gemini 1.5 Flash offers the most cost-effective performance among advanced AI models, with $0.9 per million tokens.

Artificial Analysis has carried out research regarding input and output prices. The former implies the cost per token included in the request sent to the API, and the latter – from the API.

Google Gemini statistics indicate that the Gemini 1.5 Flash value is $0.9 per million input or output tokens. It is a cost-effective option, especially when compared to other models.

For instance, Gemini 1.0 Pro is priced at $1.5 per million input or output tokens. On the higher end, GPT-4 costs $7.5 per million input tokens and $15 per million output ones. Claude 3 Opus is the most expensive, with $15 for input and $75 for output tokens.

 

Source: Artificial Analysis

Google Gemini Tech Statistics

Is Google Gemini better than ChatGPT? How does it compare to other language models regarding performance and capabilities? To answer these questions, let’s review Google Gemini statistics below. We’ll focus on the training data, context window, and benchmark performances.

 

The LaMDA model used in the former version, Google Bard, was trained on the Infinite dataset containing 1.56 trillion words and 137 billion parameters.

This massive dataset only required 750 GB of storage. It comprises 12.5% of C4-based data and an equal percentage of code documents from programming tutorials, Q&A websites, and others. Additionally, it includes 6.5% of English web documents and 6.5% of non-English web documents.

 

Gemini 1.5 Pro boasts a context window of up to two million tokens, the longest of any large-scale foundation model.

Gemini 1.5 Pro and 1.5 Flash both have a default context window of up to one million tokens. Thus, these models enable near-perfect recall on long-context retrieval tasks across many formats. The latter include long documents, lines of code, audio, video, and more. For 1.5 Pro, developers and enterprise customers can sign up to try a two-million-token context window.

 

Comparing the quality index, GPT-4 scores the highest at 100, while Gemini 1.5 Pro scores 88.

Artificial Analysis has administered the evaluation where a higher quality index indicated better language model performance. Let’s review the data in more detail.

Model
Quality Index

GPT-4.0

100

GPT-4.0 Turbo

94

Claude 3 Opus

94

Gemini 1.5 Pro

88

Llama 3 (70B)

88

Gemini 1.5 Flash

76

Claude 3 Haiku

72

GPT-3.5 Turbo

65

Llama 3 (8B)

65

As a result, we can see the comparison of Google Gemini vs GPT-4. The latter leads with a quality score of 100. Meanwhile, Gemini 1.5 Pro scores 88, showcasing robust performance.

 

Gemini 1.5 Flash is the fastest among its competitors, processing 141 tokens per second.

Google Gemini statistics show that Gemini 1.5 Flash outperforms other models speed-wise. Specifically, it processes 141 tokens per second. Llama 3 (8B) follows with 121 tokens per second, and Claude 3 Haiku processes 101 tokens per second.

Model
Tokens per Second

Gemini 1.5 Flash

141

Llama Flash

121

Claude 3 Haiku

101

GPT-4.0

74

Gemini 1.5 Pro

55

GPT-3.5 Turbo

52

Llama 3 (70B)

41

Claude 3 Opus

29

GPT-4 Turbo

23

GPT-4 processes 74 tokens per second, while Gemini 1.5 Pro – 55 tokens per second. GPT-3.5 Turbo handles 54 tokens per second.

 

Among all Gemini models, the 1.5 Pro version has the best performance. The second-best model is Gemini 1.0 Ultra.

Google Gemini statistics prove the 1.5 Pro version is the top-performing model. Google DeepMind carried out research on:

  • general performance
  • code generation
  • math problem-solving
  • reasoning – GPQA and Big-Bench Hard
  • multilingual capabilities
  • image reasoning
  • mathematical reasoning
  • audio recognition
  • video question answering

The general performance, measured by MMLU, showed Gemini 1.5 Pro achieving the highest score of 85.9%. Gemini 1.0 Pro scored the lowest at 71.8%. In reasoning tasks, as assessed by Big-Bench Hard, Gemini 1.5 Pro again led with an impressive 89.2%. Meanwhile, Gemini 1.0 Pro had the lowest score at 75.0%. For multilingual capabilities, evaluated by WMT23, Gemini 1.5 Pro topped the list at 75.3%. Again, Gemini 1.0 Pro was at the lower end with 71.7%.

Audio recognition, evaluated by FLEURS, was one of the weaker capabilities across all models. Gemini 1.5 Flash had the highest score of 9.8%, while Gemini 1.0 Pro had the lowest at 6.4%. Reasoning abilities, measured by GQPA, showed the best performance with Gemini 1.5 Pro at 46.2%. At the same time, Gemini 1.0 Pro scored the lowest at 27.9%. For mathematical problem-solving, Gemini 1.5 Pro led with 67.7%, and Gemini 1.0 Pro lagged with a score of 32.6%.

 

Source: Google DeepMind, Artificial Analysis

Google Gemini Timeline

How has Google Bard evolved into Gemini? What key milestones mark this transformation? The timeline below shows the development and enhancement stages of this language model. Let’s take a closer look.

01
February 6, 2023
Google announced the future release of Bard.
02
March 21, 2023
Bard access was opened to the public.
03
April 10, 2023
Experiment updates page was added with the 'Google it' option. Moreover, updated Bard capabilities were introduced.
04
April 21, 2023
Bard began supporting 20 programming languages, and drafts were added.
05
May 5, 2023
Bard gained access to Google Workspace accounts.
06
May 10, 2023
Bard became available in Japanese and Korean. It could now export content to Google Docs or Gmail. A dark theme was also launched.
07
May 15, 2023
Bard's summarization capabilities were improved. It began displaying sources for its responses.
08
May 23, 2023
Bard could now display help images along with relevant responses.
09
June 1, 2023
Bard provided more relevant responses with location.
10
June 7, 2023
Bard started coding and improved in math and data analysis. Users could export Bard tables to Google Sheets.
11
July 13, 2023
Bard became available in 40 more languages and 27 more countries. Google Lens was added to Bard. Users could ask Bard to read out responses and view pinned and recent threads. Moreover, they could share Bard conversations with others and modify responses. Last but not least, developers could export Python code to Replit.
12
September 19, 2023
Bard could now connect to Google apps and services. Thus, double-checking of responses and accessing features in more places were enabled.
13
December 6, 2023
Google introduced Gemini, their most prominent and capable AI model.
14
February 1, 2024
Gemini Pro in Bard became available in over 40 languages and more than 230 countries and territories. Image generation also became possible.
15
February 8, 2024
Bard was rebranded, and the Google Gemini app was introduced. Also, this day was the Google Gemini Ultra release date.
16
May 14, 2024
Google launched Gemini 1.5 Pro to Gemini Advanced subscribers in over 35 languages. It featured a 1 million token context window and a new conversational experience. Moreover, tools that let Gemini take action on users' behalf were introduced.

As we can see, Google expands its AI capabilities and reach with each update.

Summing up

The Google Gemini statistics reveal a robust and versatile language model that excels in various capabilities. With its comprehensive training data and advanced context window, Gemini stands as a competitor to ChatGPT and other leading models.

As seen, Google’s solution offers advanced capabilities and versatile performance across multiple domains. Gemini 1.5 Pro, for instance, excels in general knowledge, code generation, and mathematical reasoning. Additionally, its context window of up to two million tokens sets it apart from its counterparts.

Google Gemini is poised to influence businesses significantly. Its advanced AI capabilities can enhance various operations, from customer service to data analysis. Thus, companies might be able to drive efficiency and innovation.

Are you looking to develop a custom language model? Don’t hesitate to contact DOIT Staffing. Our team of experts is ready to help you harness the power of the latest AI technologies. Enhance your operations and engage your customers more effectively today!

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How many people use Google Gemini?

Google Gemini statistics reveal there were 60.05 million unique visitors in April 2024 alone.

ChatGPT, Google Bard, and Anthropic Claude are examples of which type of generative AI model?

ChatGPT, Google Bard, and Anthropic Claude are examples of large language models (LLMs). They are designed to generate human-like text based on the input they receive. Thus, they are capable of tasks such as text generation, translation, summarization, etc.

Why did Google change Bard to Gemini?

Google rebranded Bard to reflect the significant advancements made to the AI model. In the Google Bard vs Gemini comparison, the latter has improved performance. Moreover, the new version has broader functionalities. This rebranding also aligns with Google’s strategy to continuously innovate and provide state-of-the-art AI solutions.

How up-to-date is Gemini?

Google Gemini is up-to-date with information and knowledge available up to early 2023. It might not have information on events that have occurred after that point.

Anna Ivashyna,
Project Manager @ DOIT Software
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