Google announced the Gemini, its latest multimodal AI, on Dec 6, 2023. Google Gemini shines with its high performance and ability to process different types of data as input or output. When it comes to text, image, video, and audio benchmarks of Google Gemini, it is possible to say that it has higher scores than GPT-4.
In this article, we will compare Google's Gemini and OpenAI's GPT-4 and explore their similarities and differences.
- Google Gemini is Google's most advanced AI multimodal, announced on Dec 6, 2023.
- You can visit Google Products or Google Gemini to access Gemini.
- Google boosted context window capacity of Gemini 1.5 Pro to 1 million tokens, available for select users via AI Studio and Vertex AI.
- Both Google's Gemini and OpenAI's GPT-4 models support data in image, text, code, video, and audio types.
- Google Gemini has a higher score than GPT-4 in reasoning and math benchmarks.
- Google Gemini has higher performance than GPT-4 in code generation and problem-solving tasks.
- When it comes to customization, GPT-4 offers limited options, while Gemini does not have any customization options.
- If you are looking for a state-of-the-art AI assistant for your daily, business or writing tasks, TextCortex is the way to go with its interactive and customizable features.
Google Gemini is a cutting-edge AI product announced by Google that can process different types of data, such as text, visuals, videos, and audio. Google Gemini comes in three different sizes: Nano, Pro, and Ultra. While the Google Gemini Ultra model is designed to complete complex tasks with high accuracy, the Gemini Pro model is designed to power AI tools, and the Gemini Nano model is designed to work on mobile devices.
Google Gemini Performance
Gemini Ultra has higher scores than GPT-4 in benchmarks. Although the Gemini Ultra model is not publicly available at the moment, its performance in benchmarks and multimodality promises that it will be effective in a wide range of areas.
The Google Gemini Pro model has high performance and powers Google Bard. It can also be accessed by users since it is available on Google Products. Last but not least, the Gemini Nano model does not have as high performance as others, it works on mobile devices without the need for any external server.
Gemini 1.5 Pro
Gemini 1.5 Pro model normally contains a context window consisting of 128,000 tokens. However, as of today, a select group of developers and enterprise customers can test it using a context window with a capacity of up to 1 million tokens, via AI Studio and Vertex AI in a private preview.
Thanks to several machine learning advances, Google has drastically amplified the 1.5 Pro's context window limit from its original capacity of 32,000 tokens for Gemini 1.0. The updated version can now handle up to 1 million tokens during production.
How to Access Google Gemini?
There are two methods to access Google Gemini models.
1. The first of these is Google Products, where you can access Gemini Pro and Gemini Nano models. From here, you can experience two Gemini sizes and observe their performance firsthand.
2. Another method to access the Gemini Pro model is through this link. Gemini (ex. Bard) currently utilizes the Gemini Pro model in the free version. You can upgrade to Gemini Advanced for $19.99.
The Google team is currently completing extensive safety checks to add the Gemini Ultra model to the Bard AI chatbot. Afterwards, Gemini Ultra will be launched into the beta process through Bard AI and will be available.
Is Google Gemini free?
Google Gemini Pro and Nano models are free to use. You can also experience the Google Gemini Pro model through Google Gemini website and test its advanced reasoning, math, and language understanding skills.
Gemini also offer a premium subscription named Gemini Advanced priced at $19.99 USD.
Google’s Gemini vs OpenAI’s GPT-4
Google Gemini is a grand rival to OpenAI's GPT-4 model with its advanced reasoning, math, language understanding, and coding skills. The Gemini Ultra model managed to surpass GPT-4 in most of the text, coding, visual, audio, and video benchmarks. Let's compare Google's Gemini and OpenAI's GPT-4 together!
Reasoning and Math
The Google Gemini model has state-of-the-art performance in 30 of the 32 academic benchmarks used in large language models (LLMs). Thanks to these benchmarks, we can observe the mathematical reasoning performance of the Gemini Ultra model. The Gemini Ultra model has higher scores than GPT-4 in various reasoning benchmarks, such as Big-Bench Hard, GSM8K, and MATH, except for HellaSwag, which represents commonsense reasoning.
In other words, Google Gemini has better performance than GPT-4 in all reasoning tasks except for common sense reasoning tasks.
When it comes to multimodality, both language models can process text, code, visual, audio, and video types of data. In other words, by using both AI models, you can analyse, process, and use different types of data.
When we inspect the image, video, and audio benchmarks of the two large language models, we see that the Google Gemini Ultra model has higher scores, up to 10%, than GPT-4. That means, the Gemini Ultra model is more advanced and successful in multimodality tasks than GPT-4.
Google Gemini is an AI model that has advanced coding skills and can use advanced reasoning and logic to solve complex coding problems. Moreover, Google Gemini can be used as an engine in advanced coding systems as it completes complex and advanced coding tasks with a high accuracy rate.
The Google Gemini Ultra model has higher scores than GPt-4 in the HumanEval and Natural2Code benchmarks used to measure the coding performance of AI tools. This means that the Google Gemini model is more functional in coding and math tasks than the GPT-4 model.
Both the GPT-4 and the Gemini Nano and Pro models are publicly accessible. But when it comes to Gemini Ultra, you can't access it right now. The main reason for this is that the security and reliability checks of the Gemini Ultra model have not been completed yet. Considering all these, we can say that the GPT-4 model is one step forward in accessibility.
If you want to turn an AI tool into your personal assistant, you should take a look at its customization options. While OpenAI offers limited customization options for knowledge base and personality with the GPT-4 model, Gemini does not have any customization options.
Although the GPT-4 large language model has more customization options than Gemini, it is not possible to say that it offers a fully customized AI experience. If you are looking for an AI tool that offers a fully customizable AI experience, you should consider trying TextCortex.
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