Gemini AI Launched – How to use Gemini AI?

Updated on February 14 2024

On 6th December, 2023, Sundar Pichai, the CEO of Google, did an interesting announcement.

He announced the launch of Gemini AI, a new LLM from Google which is known to be the best of all yet.

Google Gemini was teased by Pichai in I/O developer conference in June 2023.

In the launch, Google showed how Gemini was able to update a chart by analyzing hundreds of pages and analyzing a math homework from a picture and identifying the correct answers while pointing out the wrong ones.

While this all has been done before, bringing it on this scale will be a big leap in artificial intelligence. While, the Gemini is not yet accessible, you can get a gist of it on Google Bard.

Here is everything that we know about Google’s latest LLM, Gemini.

How to use Gemini AI?

Google AI Studio
Google AI Studio

Let’s start with the most curious question – how to access Google Gemini AI?

Google started providing access to updated Gemini Pro to developers and enterprises on 13th December through Google AI studio. Here is how you can integrate Gemini AI on your app:

1. Prerequisites:

Technical Understanding: You need a strong understanding of programming languages, API integrations, and software development principles.

Google AI Account: You need a Google Cloud Platform account with access to Google Cloud and AI Studio (You can migrate to Vertex AI later as we have explained in the next section of this article).

App Development Environment: Your app needs to be developed in a compatible environment like Python or TensorFlow.

2. Access Gemini Pro in AI Studio:


Navigate to Google AI Studio: Sign in to your Google Cloud Platform account and access Google AI Studio.

Locate Gemini Pro: Search for and select the Gemini Pro service within the AI Studio interface.

Request Access: Click on the “Request Access” button and provide details about your intended use case.

Await Approval: Google will review your request and grant access if approved.

3. Integrate the Google Gemini API:

Obtain API Keys: Once access is granted, you’ll receive Google Gemini API keys and documentation to interact with the Gemini Pro API.

Configure API Access: In your app’s code, incorporate the Google Gemini API keys and authentication methods for secure communication with Gemini Pro.

Design Data Flow: Define how data will be sent from your app to Gemini Pro and how the response will be processed within your app.

4. Implement Features:

Utilize Gemini Pro Capabilities: Leverage specific functionalities of Gemini Pro relevant to your app, such as text generation, image recognition, or code completion.

Handle Responses: Integrate the received responses from Gemini Pro into your app’s user interface and logic.

Test and Refine: Test your app thoroughly to ensure seamless integration and desired outcomes.

5. Monitor and Maintain:

Monitor Performance: Track your app’s interaction with Gemini Pro and identify any potential issues or areas for improvement.

Manage Usage: Monitor your Google Gemini API usage and costs to ensure optimal resource utilization.

Stay Updated: Keep yourself informed about updates to the Gemini Pro API and incorporate them into your app as needed.

How to Migrate from AI Studio to Vertex AI with Gemini AI Data?

Vertex AI is Google’s all-in-one workshop for building and deploying your AI ideas, from coding to pre-built tools. It allows more customization to the AI. You can get full control on the your Gemini AI API data and get better security. If you are sure to scale your AI application you made with Google Gemini API, you should migrate to Vertex AI.

Here is how to migrate from AI Studio to Vertex AI on Google Cloud:

  • Step 1: Create a Google Cloud project or use an existing one.
  • Step 2: Enable billing on your project and set up a Vertex AI Studio instance.
  • Step 3: Download your prompts from your Google Drive AI Studio folder and save them as a JSON file.
  • Step 4: Upload the JSON file to Vertex AI Studio.
  • Step 5: Upload your training data to a Google Cloud Storage bucket.
  • Step 6: Start using Vertex AI Studio to train and deploy your models.

But why Should you Migrate from AI Studio to Vertex AI for Gemini AI?

Some of the main reasons to migrate to Vertex AI are:

  • Production-ready Deployment: Scale and secure your Gemini applications for real-world use with enterprise-grade features.
  • Streamlined MLOps: Manage the entire AI lifecycle – training, tuning, deployment, monitoring – through one platform.
  • Multimodal Capabilities: Go beyond text with Vertex AI, leveraging Gemini’s ability to handle images, code, and audio.
  • Access to More Tools and Models: Vertex AI offers a broader ecosystem of AI tools and pre-trained models to enhance your solutions.

Additionally, you also get comprehensive monitoring, cost control, and flexible billing options for your AI projects in Vertex AI.

How to use Gemini AI in Bard?

bard using Google Gemini AI Model
Bard using Google Gemini AI

Google announced that Bard, its chatbot tool and a competitor to OpenAI’s ChatGPT, will start using Gemini model from today. Even on the Bard access page, you can now see a message from Google about Bard using Gemini. However, it does not yet provide the ability to upload videos or audios and ask related questions.

Here is what Bard responded when asked to provide information about the font used in one of Appscribed’s featured images-

Google Bard not able to understand images yet
Google Bard not able to understand images even after Gemini update

Hence, all the Google Gemini features are yet to be added in Bard but you can use Google Gemini AI in Google Bard simply by:

  1. Sign up: Head to and create a free account.
  2. Open Chat: Click “Start a chat” and begin a text conversation.
  3. Get Specific: Use clear prompts like “Summarize this article using Gemini” or “Write a song like Taylor Swift powered by Gemini” (I have personally noticed that results are quite different when Bard to use Gemini but there is no guideline by Google about it)
  4. Explore Prompts: See Bard’s suggestions for Gemini prompts in the chat.

What is Google Gemini AI Model?

Google Gemini AI is an artificial intelligence model developed by Google DeepMind, which claims to outperform previous models like ChatGPT in various tests and displays advanced reasoning capabilities. Gemini is built for multimodality, meaning it can reason seamlessly across text, images, video, audio, and code. It is available in three sizes: Gemini Nano, Gemini Pro, and Gemini Ultra, with each version having different levels of capabilities and applications.

Gemini AI Plans Compared – Gemini Nano vs Gemini Pro vs Gemini Ultra

FeatureGemini NanoGemini ProGemini Ultra
EfficiencyMost efficientEfficientModerately efficient
Offline capabilitiesYesNoNo
StrengthsOn-device tasks, limited resourcesVersatility, wide range of tasksHigh performance, complex tasks
WeaknessesLimited capabilitiesLess efficient than NanoNot publicly available yet
Available onPixel 8 Pro, Android 14 (future)Google Generative AI Studio, Vertex AINot yet available
Current use casesAudio summarization, smart repliesBard, various Google productsFuture applications

How Google Gemini AI work?

Google gemini vs traditional llm
Google Gemini vs Traditional LLM

Gemini works differently than the other existing LLM models. While other LLMs go through a certain type of data and stich together an output that is only available in form. However, Gemini AI works differently. It stiches an output made out of different formats of the available data.

An example of this would be that if you ask ChatGPT “what is Appscribed”, it might just answer as “Appscribed is a SaaS review platform featuring over 200 SaaS apps…” However, Gemini’s approach would be to go through different sources including pictures, codes, videos, audios, and give you the best output as a mixture of all or as one that is the best.

Features of Google Gemini

Multimodal Processing: Unlike most AI models that primarily handle text data, Gemini excels in processing and understanding various modalities, including text, images, code, audio, and video. This allows it to tackle complex tasks requiring information integration from diverse sources.

Highly Efficient Integration: Gemini is designed for seamless integration with existing tools and APIs, making it readily accessible and adaptable for developers to leverage its capabilities within their own projects. This facilitates the development of innovative AI applications and tools.

Future-Proof Design: Built with future advancements in mind, Gemini incorporates memory and planning functionalities, paving the way for even more sophisticated applications. This ensures that the model remains relevant and adaptable to future technological developments in the field of AI.

Unprecedented Performance: Early demonstrations showcase Gemini’s impressive capabilities exceeding what previous models have achieved. For instance, it can analyze a screenshot of a chart, gather related research articles, and automatically update the chart with the new information. This demonstrates a level of understanding and manipulation of data not seen before.

Surpassing Human Expertise: Gemini Ultra, the most advanced version, has set a new benchmark by achieving a score of 90.0% on the MMLU test, surpassing human experts across diverse subjects. This signifies a significant leap in AI performance and intelligence, indicating a potential to revolutionize various fields.

Is Gemini AI better than GPT 3.5 and GPT 4?

The Pro version of Gemini reportedly outperforms OpenAI’s GPT 3.5 in certain aspects, but it is the more powerful Ultra version that claims to surpass all existing AI models. In a benchmark test, Gemini Ultra achieved an impressive 90 percent score, surpassing the human “expert level” benchmark of 89.8 percent. This marks the first time an AI has outperformed humans in this test, showcasing the model’s advanced capabilities. In comparison, GPT-4 scored 87 percent in the same test. However, CNBC reported that the company dodged the questions on comparison with GPT4.

How is Google Launching Gemini AI?

Google is launching its flagship AI model, Gemini, in a phased approach:

Launch Announcement (December 7, 2023)

Google announced to launch Gemini AI with limited access for developers and enterprises. The public beta and widespread availability are still in the planning stages but is accessible in Google Bard. Moreover, Google Gemini Nano is also reportedly coming to Google Pixel 8 phone and later in all the Android phones as well.

Phase 1: Limited Access for Developers and Enterprises (December 13, 2023)

Gemini Pro, an advanced version, is available through the Gemini API in Google AI Studio and Google Cloud Vertex AI. This phase targets developers and enterprise customers who want to integrate Gemini into their products and workflows.

Phase 2: Public Beta Release (Date Undetermined)

A public beta version of Gemini will be made available to a wider audience. This will allow individuals to experiment with Gemini and experience its capabilities firsthand. Google has not yet announced a specific date for the public beta release.

Phase 3: Widespread Availability (Date Undetermined)

After gathering feedback from developers and the public, Google will make Gemini available for broader use. This could include integrating Gemini into Google products and services, such as Search, Assistant, and Pixel devices. The timeframe for this phase is also unclear.

Why Google launching Gemini in Phases?

Some of the reasons why Google is launching Gemini AI in phases are-

Complexity of the Technology: Gemini is a complex AI model that requires careful testing and refinement before being released to a wider audience.

Need for Feedback: Google wants to gather feedback from developers and the public to ensure that Gemini is meeting their needs and expectations.

Avoiding Potential Issues: A phased launch allows Google to identify and address any potential issues before they impact a larger group of users.

What is Bard Advanced and when is it launching?

Google recently unveiled Bard Advanced, representing a major upgrade powered by their new Gemini AI technology. While full general public access to Gemini AI is still under development, users will be able to get early access to innovations like Bard Gemini Pro anticipating broader rollout in 2024.

Integrating Gemini’s advanced natural language capabilities, Bard Advanced introduces features like generating creative text formats such as poems, code, and emails that surpass existing systems. The new model also enables seamless integration with Google services, allowing users to leverage Bard for tasks like simplified science explanations and marketplace listings.

As Gemini API access expands, Bard Advanced promises heightened accuracy and reliability through cross-verification features. With plans to increase accessibility to more countries and languages, the launch of Bard Advanced hints at the next evolution of AI, driven by Google’s powerful new Gemini technology.


Google Gemini AI will indeed be a big leap in the AI industry. With us being able to get better outputs, we will have more productivity and get you more content on Appscribed. Moreover, for developers, getting access to Gemini AI Pro, Nano and Ultra will unlock a lot of potential. We will be seeing a lot of new AI tools with advanced capabilities in 2024.

Also Read: We asked the Public and AI Chatbots to Predict the Future of AI in 2024 and they all have an interesting take on it

FAQs on Gemini AI

What is Google Gemini AI, and when was it announced?

Google Gemini AI is a new and most advanced large language model announced by Sundar Pichai, the CEO of Google, on December 6, 2023.

How can developers and enterprises access Gemini Pro?

Developers and enterprises can access Gemini Pro through Google AI Studio. They need to have a strong technical understanding, a Google Cloud account, and an app developed in a compatible environment like Python or TensorFlow.

Why should you migrate from AI Studio to Vertex AI with Gemini AI?

Migrating to Vertex AI offers production-ready deployment, streamlined MLOps, multimodal capabilities, access to more tools and models, comprehensive monitoring, cost control, and flexible billing options.

How can Gemini AI be used in Google Bard?

Users can access Gemini AI in Google Bard by signing up on, starting a text conversation, and using clear prompts like “Summarize this article using Gemini” or “Write a song like Taylor Swift powered by Gemini.”

What are the different versions of Google Gemini AI, and how do they compare?

Gemini is available in three sizes: Nano, Pro, and Ultra. The article provides a detailed comparison of their features, strengths, weaknesses, and current use cases.

How does Gemini AI differ from traditional language models like GPT 3.5 and GPT 4?

Gemini works by stitching together outputs made from different formats of available data, including text, images, code, audio, and video. It is designed for multimodal processing, going beyond the capabilities of traditional language models.

What is Bard Advanced, and when is it launching?

Bard Advanced is an upgrade powered by Gemini AI technology, offering features like generating creative text formats and seamless integration with Google services. While full public access to Gemini AI is still under development, Bard Advanced is expected to roll out more broadly in 2024.

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