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.
As of December 2025, Gemini includes previous Gemini 2.0 (Flash & Flash-Lite), Gemini 2.5 Flash, Flash-Lite, and Pro, and the newest Gemini 3 Pro & Flash.
In this article, you’ll find out the detailed Google Gemini statistics. We’ll 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.
Below are the most notable Google Gemini stats:
Let’s go over the key details of this language model launched by Google:
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
Model variants
Gemini 3 Pro: For multimodal understanding, vibe-coding, and agentic tasks
Gemini 3 Flash: For speed, combining frontier intelligence with superior search and grounding
Supported data types for input
Text, Image, Video, Audio, PDF
Knowledge cutoff
January 2025 (Gemini 3 Pro)
Supported # tokens for input
1M (Gemini 3 Pro)
Websites Like Gemini
ChatGPT, Claude, Grok, DeepSeek
Source: Google AI for Developers, Google DeepMind
Now that we got to know what Google Gemini is, let’s move into the usage stats.
Google Gemini attracts millions of users globally. Let’s review its performance in several key usage trends.
Gemini had 1.2 billion total monthly visits in October 2025
In October 2025, Google Gemini statistics showed 813.2 million visits on desktop and 368.8 million visits on mobile. Visits peaked this month with 1.182 billion total (a 11.74% increase from September 2025).
Especially, mobile traffic has been increasing in recent months. Specifically, there were 393.6 million mobile visits in September 2025, a 106.8% increase from 190.3 million mobile visits in August 2025.
Aug 2025
533M
190.3M
723.3M
-
Sep 2025
664.2M
393.6M
1.057B
+46.24%
Oct 2025
813.2M
368.8M
1.182B
+11.74%
In the Claude vs Google Gemini vs ChatGPT comparison, the latter dominates in total visits. In October 2025, ChatGPT had an impressive 6.2 billion total visits. It significantly outpaced Google Gemini’s 1.2 billion. Meanwhile, Claude recorded 197 million.
Google Gemini attracted 206.4 million unique visitors in October 2025
In August 2025, the platform had 122.1 million unique visitors overall. There was a great increase, with unique visitors rising to 207.6 million by September (+69.97%).
Gemini number of users on desktop started at 72.69 million in August 2025 and increased slightly to 104.3 million in October 2025. Meanwhile, mobile unique visitors rose from 49.49 million to 102 million over the same period.
Google Gemini’s bounce rate of 28.96% is one of the lowest among competitors
Google Gemini statistics by month show a relatively stable bounce rate with slight fluctuations. In August 2025, the desktop bounce rate was 28.46%. The value decreased slightly to 27.24% by October 2025. The mobile indicator decreased significantly from 41.52% in August to 32.76% in October.
Aug 25
28.46%
–
41.52%
–
Sep 25
27.13%
-4.67%
30.3%
+0.41%
Oct 25
27.24%
-27.02%
32.76%
+8.12%
Gemini users viewed an average of 4.52 pages per visit in October 2025
Engagement on Google Gemini is evident in the pages-per-visit metric. Desktop users visited an average of 3.45 pages per session in October 2025.
Mobile users are significantly more engaged than desktop users with Google Gemini, viewing nearly twice as many pages per session. Mobile users averaged 4.72 pages per visit in August 2025, ending at 6.87 pages per visit in October.
Aug 25
3.29
–
4.72
–
Sep 25
3.52
+6.91%
7.98
+69.13%
Oct 25
3.45
-1.75%
6.87
-13.91%
The average visit duration for Gemini was 7 minutes and 08 seconds in October 2025
The average visit duration for desktop users was 5 minutes and 15 seconds in August 2025. It slightly increased to 5 minutes and 30 seconds by October. Mobile users had a longer visit duration. Specifically, it started at 8 minutes and 25 seconds and ended at 10 minutes and 46 seconds in October 2025.
Aug 25
0:05:15
–
0:08:25
–
Sep 25
0:05:35
+6.53%
0:11:03
+31.2%
Oct 25
0:05:30
-1.72%
0:10:46
-2.64%
Google Gemini shows improved engagement, but ChatGPT is a leader
According to the latest Google Gemini statistics as of October 2025, the platform has significantly improved its engagement metrics.
Google Gemini now averages 4.52 pages per visit, surpassing both ChatGPT (3.84) and Claude (3.93). Gemini also leads in average visit duration at 7 minutes 8 seconds, compared to ChatGPT’s 6 minutes 25 seconds and Claude’s 5 minutes 59 seconds.
Gemini has improved its bounce rate to 28.96%, performing better than ChatGPT (31.18%) but slightly behind Claude (29.46%).
However, ChatGPT still dominates in user retention with 12.74 visits per unique visitor, followed by Claude at 9.78 and Gemini at 5.73. This metric indicates that while Gemini users engage deeply during individual sessions, they return less frequently than users of competing platforms.
In terms of total traffic, ChatGPT continues to lead by a significant margin with 6.165 billion monthly visits, followed by Gemini at 1.182 billion and Claude at 196.9 million.
Monthly visits
1.182B
6.165B
196.9M
Monthly unique visitors
206.4M
483.7M
20.13M
Visits / Unique visitors
5.73
12.74
9.78
Visit duration
0:07:08
0:06:25
0:05:59
Pages per visit
4.52
3.84
3.93
Bounce rate
28.96%
31.18%
29.46%
Page views
5.343B
23.68B
774.3M
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, 32.2% of its user base is on mobile devices. In contrast, ChatGPT has a higher desktop usage at 70.3%, while only 29.7% of its users are on mobile. Similarly, Claude has 89.4% of its users on desktop and only 10.6% on mobile.
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.
Source: SimilarWeb, My Learning
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 October 2025
As of October 2025, the United States led the traffic sources for Google Gemini with 12.99%. India followed with 8.82%, Brazil with 7.53%, Japan with 6.55%, and Indonesia with 6%. The rest of the world contributed 58.11% of the traffic.
The largest age group of Google Gemini users is 25-34. It makes up 29.7% of the audience
Google Gemini statistics highlight that the 25-34 age group is the most significant demographic. It comprises 29.7% of the audience. The 18-24 age group follows with 22.4%, while the 35-44 group accounts for 19.7%. Smaller segments include the 45-54 group at 14%, the 55-64 group at 8.9%, and users aged 65 and above at 5.3%.
Male users represent 57.82% of Google Gemini’s audience
Gender distribution data indicates that male users dominate the platform. This segment made up 57.82% of the audience. Meanwhile, the female counterparts constitute 42.18%.
Direct traffic to Google Gemini peaked at 894 million in October 2025
Direct traffic peaked at 894 million in October 2025, up from 536.2 million in August 2025. Overall, direct traffic accounts for 75.64% of traffic from marketing channels on Google Gemini.
The second-largest traffic source is organic search, which accounted for 13.97% of traffic, or 165.1 million, in October 2025. This is followed by paid search (4.43%), referrals (4.36%), and social media (1.26%).
Direct
894.1M
75.64%
Organic
165.1M
13.97%
Paid
52.4M
4.43%
Referrals
51.5M
4.36%
Social
14.9M
1.26%
Display ads
2.6M
0.22%
1.4M
0.12%
Source: SimilarWeb
Let’s explore Google Gemini’s cost structure and compare it with other language models.
Gemini 3 Flash offers one of the most cost-effective performances among advanced AI models, with $0.50 (input) and $3 (output) 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 3 Flash value is $0.5 per million input or $3 per million output tokens.
For instance, Gemini 3 Pro is priced at $2 per million input or $12 per million output tokens. GPT 5.2 costs $1.75 per million input or $14 per million output tokens. On the higher end, both Claude 4.5 Sonnet and Grok 4 cost $3 per million input tokens and $15 per million output ones.
Source: Artificial Analysis
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 3 Pro boasts a context window of up to one million tokens
Gemini 3 Pro and 3 Flash both feature a context window of up to one million tokens, matching Claude 4.5 Sonnet and Grok 3. This positions them among the leaders in long-context processing capabilities. Grok 4 Fast extends this further with a two-million-token context window, currently the largest available.
These models enable near-perfect recall on long-context retrieval tasks across multiple formats, including long documents, lines of code, audio, video, and more.
By comparison, other leading models offer smaller context windows: GPT-5 supports up to 400,000 tokens, Grok 4 handles 256,000 tokens, and Claude 4.5 Haiku processes 200,000 tokens.
Comparing the Artificial Analysis Intelligence Index, Gemini 3 Pro scores the highest at 73, while Gemini 3 Flash scores 71
Artificial Analysis has administered the evaluation that incorporated 10 evaluations spanning reasoning, knowledge, math & coding. Let’s review the data in more detail.
Gemini 3 Pro
73
GPT-5.2
73
Gemini 3 Flash
71
Claude 4.5 Opus
70
GPT 5.1
70
Kimi K2 Thinking
67
Grok 4
65
Claude 4.5 Sonnet
63
As a result, we can see the comparison of Google Gemini vs GPT-5. GPT-5.2 leads the pack with a score of 73, the same as Gemini 3 Pro, demonstrating the strongest overall performance across reasoning, knowledge, math, and coding tasks.
Gemini 3 Flash is the fastest among its competitors (after gpt-oss-120B), processing 207 output tokens per second
Google Gemini statistics show that Gemini 3 Flash outperforms other models speed-wise. Specifically, it processes 207 tokens per second. GPT 5.2 (xhigh) follows with 147 tokens per second, and Gemini 3 Pro processes 132 tokens per second.
gpt-oss-120B
330
Gemini 3 Flash
207
GPT 5.2
147
Gemini 3 Pro
132
Llama 4 Maverick
131
Nova 2.0 Pro
123
Kimi K2 Thinking
82
Claude 4.5 Sonnet
70
Claude Opus 4.5
64
Grok 4
28
Among all Gemini models, the 3 Pro version has the best performance
According to the latest benchmarks, Gemini 3 Pro demonstrates competitive capabilities across multiple evaluation categories.
The model achieves 96% on AIME ’25, matching GPT-5.1 Codex. This rank places it in the upper tier for mathematics. However, it trails behind GPT-5.2 (99%).
In science, Gemini 3 Pro ranks first and, as of late December 2025, scores 91% on GPQA Diamond.
Also, with 90% on MMMU-Pro, Gemini 3 Pro performs well on tasks combining vision and text. It matches the results of Claude Opus 4.5, together holding the first position.
Here is a detailed table about Google Gemini benchmarks compared to other popular models:
Humanity's Last Exam
37.2%
31.4%
28.4%
23.9%
22.3%
GPQA diamond (Science)
91%
90%
87%
88%
84%
AIME ‘25 (Mathematics)
96%
99%
91%
93%
95%
LiveCodeBench (Coding)
92%
89%
87%
82%
85%
MMMU-Pro
90%
87%
90%
87%
85%
AA-LCR (Long context reasoning)
71%
73%
74%
68%
66%
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.
As you can see, Google expands its AI capabilities and reach with each update. Recent improvements have focused on enhanced formatting, better image understanding, reasoning for homework help, and deeper integration across Google’s ecosystem.
In November 2025, Google updated Gemini with a 3 Pro model with improved multimodal understanding and efficiency. December brought Gemini 3 Flash, a new, most intelligent update for speed.
This next generation promises even more powerful AI agent capabilities and represents Google’s continued push to compete with GPT-5 and Claude 4.
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 3 Pro, for instance, excels in mathematics, science, coding, and multimodal understanding. Additionally, its context window of up to one 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.
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Google Gemini statistics reveal there were 206.4 million unique visitors in October 2025 alone.
ChatGPT, Gemini, 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.
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.
Google Gemini is up-to-date with information and knowledge available up to early 2025. It might not have information on events that have occurred after that point. However, Gemini can access real-time information via Google Search integration, enabling it to retrieve current data and answer questions about recent events beyond its training cutoff.
