Gemini is a family of AI models and the name of Google’s generative AI product. These models come in three different sizes and are being incorporated into several Google products, including Gmail, Docs and its search engine.
What is Google Gemini?
Gemini is a family of AI models created by Google to power many of its products, including its chatbot, also named Gemini, as well as Gmail, Docs and its search engine.
Gemini is multimodal, meaning its capabilities span text, image and audio applications. It can generate natural written language, transcribe speeches, create artwork, analyze videos and more, although not all of these capabilities are yet available to the general public. Like other AI models, Gemini is expected to get better over time as the industry continues to advance.
What Is Google Gemini?
Gemini is Google’s family of multimodal foundation models and the name of the company’s generative AI chatbot. Google is integrating Gemini across several of its products and sees it as the answer to OpenAI’s GPT-4, the multimodal large language model (LLM) that powers the paid version of ChatGPT, which kicked off a generative AI arms race that has sent several tech companies scrambling to bring the latest and greatest products to market.
Launched in December of 2023, Gemini is Google’s largest and most capable model to date, according to the company. It was developed by Google’s AI research labs DeepMind and Google Research, and is the culmination of nearly a decade of work.
Gemini Models
The model comes in four different versions, which vary in size and complexity:
Gemini 1.0 Ultra
Gemini 1.0 Ultra is the largest model for performing highly complex tasks, according to Google. The company says it is the first model to outperform human experts on a benchmark assessment that covers topics like physics, law and ethics. The model is being incorporated into several of Google’s most popular products, including Gmail, Docs, Slides and Meet. For $19.99 a month, users can access Gemini 1.0 Ultra through the Gemini Advanced service.
Gemini 1.5 Pro
Gemini 1.5 Pro is the middle-tier model designed to understand complex queries and respond to them quickly, and it’s suited for “a wide range of tasks” thanks to an expanded context window for improved memory and recall. A specially trained version of Pro powers the AI chatbot Gemini and is available via the Gemini API in Google AI Studio and Google Cloud Vertex AI.
Gemini 1.0 Nano
A much smaller version of the Pro and Ultra models, Gemini 1.0 Nano is designed to be efficient enough to perform tasks directly on smart devices, instead of having to connect to external servers. 1.0 Nano currently powers features on the Pixel 8 Pro like Summarize in the Recorder app and Smart Reply in the Gboard virtual keyboard app.
Gemini 1.5 Flash
The latest member of the Gemini family, Gemini 1.5 Flash is a smaller version of 1.5 Pro and built to perform actions much more quickly than its Gemini counterparts. 1.5 Flash was trained by 1.5 Pro, receiving 1.5 Pro’s skills and knowledge. As a result, this model has the context window to handle hefty tasks while serving as a more cost-efficient alternative to larger models.
What Can Google Gemini Do?
Gemini is a multimodal model, so it is capable of responding to a range of content types, whether that be text, image, video or audio.
Generate Text
Gemini can generate text, whether that’s used to engage in written conversations with users, proofread essays, write cover letters or translate content into different languages. Gemini can also understand, explain and generate code in some of the most popular programming languages, including Python, Java, C++ and Go.
Like any other LLM, though, Gemini has a tendency to hallucinate. “The results should be used with a lot of care,” Subodha Kumar, a professor of statistics, operations and data science at Temple University’s Fox School of Business, told Built In. “They can come with a lot of errors.”
Produce Images
Gemini is able to generate images from text prompts, similar to other AI art generators like Dall-E, Midjourey and Stable Diffusion.
This capability was temporarily halted to undergo retooling after Google was criticized on social media for producing images that depicted specific white figures as people of color. Image generators have developed a reputation for amplifying and perpetuating biases about certain races and genders. Google’s attempts to avoid this pitfall may have gone too far in the other direction, though.
Analyze Images and Videos
Gemini can accept image inputs and then analyze what is going on in those images and explain that information via text. For example, a user can take a photo of a flat tire and ask Gemini how to fix it, or ask Gemini for help on their physics homework by drawing out the problem. Gemini can also process and analyze videos, generate descriptions of what is going on in a given clip and answer questions about it.
Understand Audio
When fed audio inputs, Gemini can support speech recognition across more than 100 languages, and assist in various language translation tasks — as shown in this Google demonstration.
Streamline Workflows
Gemini can be integrated into several Google Workspace products, including Gmail, Docs and Drive. Users can query Gemini (through its chatbot interface) to find a document in their Drive and summarize it, or automatically generate specific emails. “It becomes a little bit of an assistant in that sense,” Gen Furukawa, an AI expert and entrepreneur, told Built In.
Within more specific business contexts, professionals can use Gemini to produce drafts for blog posts, emails and advertisements in Docs; generate images for Slides presentations by inputting a text prompt and selecting a visual style; and even tailor their virtual background in Google Meet with a detailed text prompt.
How Does Google Gemini Work?
At a high level, the Gemini model can see patterns in data and generate new, original content based on those patterns.
To accomplish this, Gemini was trained on a large corpus of data. Like several other LLMs, Gemini is a “closed-source model,” generative AI expert Ritesh Vajariya told Built In, meaning Google has not disclosed what specific training data was used. But the model’s dataset is believed to include annotated YouTube videos, queries in Google Search, text content from Google Books and scholarly research from Google Scholar. (Google has said that it did not use any personal data from Gmail or other private apps to train Gemini.)
After training, Gemini leveraged several neural network techniques to better understand its training data. Specifically, Gemini was built on Transformer — a neural network architecture Google invented in 2017 that is now used by virtually all LLMs, including the ones that power ChatGPT.
When a user types a prompt or query into Gemini, the transformer generates a distribution of potential words or phrases that could follow that input text, and then selects the one that is most statistically probable. “It starts by looking at the first word, and uses probability to generate the next word, and so on,” AI expert Mark Hinkle told Built In.
Gemini can also process images, videos and audio. It was trained on trillions of pieces of text, images (along with their accompanying text descriptions), videos and audio clips. And it was further fine-tuned using reinforcement learning with human feedback (RLHF), a method that incorporates human feedback into the training process so the model can better align its outputs with user intent.
By training on all these mediums at once, Google claims Gemini can “seamlessly understand and reason about” a variety of inputs, such as reading the text on a photo of a sign, or generating a story based on an illustration.
Gemini vs. GPT-4o
Both the Gemini and GPT-4o language models share several similarities in their underlying architecture and capabilities. But they also have some significant differences that impact the user experience and functionalities of their associated chatbots, Gemini and ChatGPT, respectively.
Gemini Has a Broader Context Window Than GPT-4o
Both Gemini 1.5 Pro and 1.5 Flash display increased context windows, with the former possessing a context window of up to 2 million tokens and the latter up to 1 million tokens. GPT-4o’s context window pales in comparison, landing at 128,000 tokens. Alphabet CEO Sundar Pichai has referred to Gemini’s context window as “the longest context window of any foundational model yet,” and it appears this statement is valid for the time being.
As a result, 1.5 Pro and 1.5 Flash should have a greater ability to handle dense information and challenging tasks than GPT-4o.
Gemini Has Real-Time Access to the Internet, But GPT-4o Is Catching Up
Gemini has always had real-time access to Google’s search index, which can “keep feeding” the model information, Hinkle said. So the Gemini chatbot can draw on data pulled from the internet to answer queries, and is fine-tuned to select data chosen from sources that fit specific topics, such as scientific research or coding.
Users previously had to subscribe to ChatGPT Plus to get access to a plug-in that allows them to browse Bing, a search engine owned and operated by OpenAI’s biggest partner, Microsoft. However, GPT-4o promises real-time internet access, closing the information gap between it and Gemini.
Gemini Was Trained on TPUs, GPT-4o Was Trained on GPUs
Google trained Gemini on its in-house AI chips, called tensor processing units (TPUs). Specifically, it was trained on the TPU v4 and v5e, which were explicitly engineered to accelerate the training of large-scale generative AI models. In the future, Gemini will be trained on the v5p, Google’s fastest and most efficient chip yet. Meanwhile, GPT-4o was trained on Nvidia’s H100 GPUs, one of the most sought-after AI chips today.
TPUs are designed to handle the computational demands of machine learning with more speed and efficiency than GPUs, making them an essential component of the AI industry’s future.
How Does Gemini Compare to Other LLMs?
Google’s commitment to speed has paid off in some ways, with Gemini 1.5 Flash ranking as the fastest model on the market and one of the cheapest options, second only to Meta’s Llama 3 model. However, the focus on going fast has come with a price, with 1.5 Flash falling to the middle of the pack in terms of overall quality. GPT-4o, GPT-4 Turbo, Claude 3 Opus and Llama 3 all rank ahead of 1.5 Flash in the quality index.
Ultimately, determining the best LLM depends on a user’s preferences and what they’re looking to get out of a generative AI tool. Gemini 1.5 Flash is a promising option in many respects, but users who don’t view cost-efficiency as a priority may consider other models.
How to Access Google Gemini
Gemini can be accessed in several ways:
For free: You can head to gemini.google.com and use it for free through the Gemini chatbot. Or you can download the Gemini app on your smartphone. Android users can also replace Google Assistant with Gemini.
Paid version: You can also subscribe to the Gemini Advanced service for $19.99 a month, where you can access updated versions of popular products like Gmail, Docs, Slides and Meet — all of which have Gemini Ultra built into them.
Gemini is a work in progress, so it might generate answers that are inaccurate, unhelpful or even offensive. And it retains users’ conversations, location, feedback and usage information, according to Google’s privacy policy. So users may want to avoid consulting Gemini for professional advice on sensitive or high-stakes subjects (like health or finance), and refrain from discussing private or personal information with the AI tool.
Frequently Asked Questions
What can Google Gemini be used for?
Gemini is an AI tool that can answer questions, summarize text and generate content. It also plugs into other Google services like Gmail, Docs and Drive to serve as a productivity booster. And, because Gemini is multimodal, its capabilities span across text, images and audio. So, in addition to generating natural written language, it can transcribe speeches, create artwork, analyze videos and more, according to Google.
Is Gemini better than GPT-4?
According to Google, Gemini Ultra (the model’s most advanced version) outperformed GPT-4 on the majority of the most used academic benchmarks in language model research and development, as well as various multimodal tasks. But the margins were slim, indicating that Gemini Pro (the smaller model size that powers the Gemini chatbot) likely doesn’t come out ahead of GPT-4.
Is Google Gemini free?
Gemini Pro, Google’s middle-tier model, is available for free at gemini.google.com. There is also a free mobile app. For $19.99 a month, users can access Gemini Ultra, the more powerful model, through the Gemini Advanced service.
Who made Google Gemini?
Google Gemini was made by Google DeepMind and Google Research — AI research labs and subsidiaries under the Google corporate umbrella.
How to access Google Gemini?
To access the free version of Google Gemini, smartphone users can download the Gemini app and Android users can substitute Gemini for Google Assistant. To use Gemini in chatbot form, users can head to gemini.google.com. For those who want to access Gemini Ultra, subscribe to the Gemini Advanced service.
