Now Google has finally released Google Gemini the AI model everyone’s been waiting for since
GPT 4 came out and it was a total surprise. We’ll look at the technical aspects of Gemini and
how it stacks up against GPT4.
So let’s get into it all right Gemini Google’s new AI a super smart tool that understands text
images sound videos and more all at once launched on December 6th, 2023.
It’s part of Google’s big push into AI makes it a key feature in their products there are three types of
Gemini let’s uncover these types and how they work.
Nano Version of Google Gemini
Google Gemini Nano stands out as the light version available in two sizes that are following.
- Nano 1 (1.8 billion parameters)
- Nano 2 (3.25 billion parameters)
Nano is Designed for mobile devices it will soon be previewed in Google’s AI core app through Android 14 on the Pixel 8 pro app.
Gemini Nano AI will power features like summarization within the record app and suggested replies for messaging apps on the other hand. We will discuss the pro version which is more powerful than the Nano version.
Pro Version of Google Gemini
Google Gemini Pro running on Google’s data centers powers applications like Google Bard a Chatbot similar to Microsoft’s Co-Pilot. It’s sent to Combine into various Google tools including Duet Ai Google Chrome Google ads, and Google Generative search experience.
Google Gemini Pro is positioned as more effective than GPT3.5 in tasks like brainstorming writing and summarizing content. The most powerful and fastest version of Google Gemini.
Ultra Version of Google Gemini
Google Gemini Ultra is trained to be natively multimodal it excels in comprehending nuanced information in text Code and audio. Google Gemini Ultra surpasses current state-of-the-art results
76% Solve rate.
When it checks and repairs answers will be 90% on a substantial number of benchmarks
used for LLM development around 30 out of 32. These are run by Google’s special tensor
processing unit pus that makes AI tasks Efficient cost cost-effective.
Gemini is challenging open AI’s GPT 4 and boasts higher efficiency and versatility by outperforming it in multiple areas. This AI model stands out because it can work with different types of data like text images, sound videos, and code all at the same time making it super versatile in solving complex tasks.
Most Powerful Version of Gemini AI
Now Gemini Ultra is the most powerful version of Gemini. It is designed for training and fine-tuning large and complex deep-learning models that feature many matrix calculations such as building large language models.
It has achieved human expert-level performance on the exam benchmark which is a test that
covers 57 tasks including elementary mathematics US history computer science Law and more.
Gemini Ultra scored 86.5% on average while GPT 4 scored 70% Gemini Ultra also excels at
multimodal reasoning tasks such as answering questions based on images videos or graphs
or generating summaries or reviews on multimodal inputs.
Difference Between Nano and Pro Google Gemini
Gemini Pro and Nano are smaller and cheaper versions. Google Gemini is designed for specific applications and use cases and it is ideal for a variety of uses. Such as chatbot code generation media content generation synthetic speech vision services recommendation engines personalization models among others.
Gemini Nano is ideal for personal and small-scale use such as education entertainment
gaming hobbies and social media both of these smaller models can leverage the pre-trained
models for Gemini Ultra or fine-tune them for their purposes now let’s see.
How Gemini Performs Compared to GPT?
GPT 4 benchmark for natural language understanding is superglue which stands for general
language understanding evaluation is a tough test that checks how well an AI can understand language by making it do things like reading and answering questions.
Gemini Ultra has a score of 92.3% beating GPT4’s 89.8% this means Gemini did better at reading and understanding stuff inside out of eight tests than there’s mm fusion which is about.
How Good is AI Handling Different Types of Data?
AI handles all types of data like text pictures and videos Gemini Ultra scored 81.7 which is
better than GPT 4 76.4 this shows Gemini is good at working with a mix of information
like answering questions about a picture or a video.
Alpha Code 2
A coding Challenge it’s about writing fixing and improving computer code out of 100 coding
tasks. Google Gemini Ultra scored 94.6 higher than GPT 4’s 88.2. It performed GPT 4 on 82 out of 100 coding tasks and tied with GPT 4 on the remaining 18.
Gemini showed a significant advantage over GPT 4 in tasks that involve writing and running code in Python and Java C++ as well as in tasks that involve using advanced programming concepts such as recursion loop functions and classes.
It also showed a slight edge over GPT 4 in tasks that involve writing and running code in
Now when we talk about the integration of the model. They designed to make Google products like Google Search Google Workspace and Google Bard better.
AlphaCode 2 needs to show some level of understanding. There is some level of seasoning and designing of code solutions before it can get to the actual implementation to solve (a) coding problem,” Leblond said. and it does all that with no problems.
Google’s Gemini is the most powerful and productive AI model that can solve thousands of problems in no time with an accuracy of more than 90%. On the other hand Chat, GPT-4 is the main source of information nowadays but Google Gemini breaks all the records and leaves other AI models far behind.
There are other Free AI Content Generators that are helpful but many of us are scared of wasting money that’s why we’ve stuck to the old pattern of recommendations.
In my opinion, you should try Google Gemini because it has all the features and accuracy that a human being can desire. If you like our content do appreciate our efforts and leave your valuable comments below.