Both OpenAI and Google have been locked in a stiff rivalry ever since the two tech giants launched their respective large language models and their associated chatbots. The competition between both firms will only grow further with the launch of Google Gemini and OpenAI’s GPT-4 Turbo, respectively. Both language models are purportedly some of the best in the industry and signify the rapid pace at which AI and machine learning have been proliferating following the initial launches in late 2022. The rate at which both demand and delivery are growing clearly indicates sustained proliferation and advancement in the novel tech space. Given that both models are invariably bound to compete against one another, a comparison between the two might shed light on their prospects and respective strengths.
Google Gemini boasts a family of models built for different purposes, while GPT-4 Turbo is an enhanced version of the extant and widely popular GPT-4, which has put OpenAI at the forefront of the AI race. Apart from enhanced multimodal capabilities and better natural language processing attributes, both models are also equipped with a very vast dataset, making their information more current and suited to diverse requirements. This article explores the various aspects of both advanced LLMs to understand their capabilities.
What Sets Google Gemini and GPT-4 Turbo Apart?
Both major LLMs were launched toward the end of 2023.
Google Gemini was built as a family of models to power its parent firm’s “AI-first” approach. Presently, Gemini boasts three distinct variants that have been built to cater to different requirements. Gemini Nano, Pro, and Ultra are the current variants of the LLM. Nano is the variant most suited to handheld devices; Pro has been crafted for chatbots like Google Bard, and Ultra is the largest and most capable model for advanced chatbots and other applications like big data and analytics. Following its launch, Google Bard switched to Gemini Pro from the older PaLM 2 models, which have powered numerous applications including a medical variant built to aid doctors and healthcare staff. That being said, Gemini is a highly capable model that scored 90% on the Massive Multitask Language Understanding (MMLU) test, beating even human experts.
Similarly, OpenAI’s GPT-4 Turbo is also a highly robust LLM that has been trained on more recent data to help it up its game against competitor offerings connected to the internet, or those that boast of more updated datasets. With information going up to April 2023, OpenAI has begun balancing its LLM’s innate capabilities with the relevance of information, making GPT-4 Turbo a good option for users. Interestingly, the model is cheaper compared to OpenAI’s older offerings, all thanks to the increased efficiency of functioning, leading to relatively lower operational costs. While Google Gemini might have a really impressive score on the MMLU benchmark, GPT-4 Turbo might just have the edge in multimodal processing capabilities given its integration with image generation models like Dall-E 3.
GPT-4 Turbo vs. Google Gemini: The Technical Aspects
The two flagship models are known to have performed well on key benchmarks.
Some of the core aspects of comparison between the two flagship models are listed in the below section:
1. Context Length and Dataset
GPT-4 Turbo builds on its predecessors and allows users a longer context window of up to 128K tokens in length. The default mode of the LLM allows users a context window of 32K instead. As for Gemini, the Pro variant supports a comparable 32K context window, with the Ultra counterpart potentially touted to have longer alternatives. As of now, GPT-4 Turbo might just have the edge on Google Gemini’s Pro and Nano models when it comes to processing extensive prompts. As for the dataset, Google has a clear lead, with the Gemini models being trained on nearly 65 trillion tokens, which outnumber the entire training data of the GPT models by nearly three times.
2. Multimodal Capabilities
Both language models are multimodal and offer AI writing, image detection, text generation, data extraction, and image generation features, among others. While OpenAI has largely banked on its Dall-E series of image generation models, Google has been working relentlessly on its Imagen models. Interestingly, the firm launched Imagen 2—the latest edition in the pipeline—in addition to SynthID, which is an intuitive AI image detection protocol. Given that both models are highly trained to carry out multiple tasks, only a formal benchmark test might provide conclusive results, despite GPT-4 Turbo having the lead. OpenAI’s edge in this area might also be attributed to its extensive trove of plugins, such as Advanced Data Analysis, which essentially makes its LLMs fit for broad data analysis use cases.
3. Usage and Performance
GPT-4 Turbo is a single model built to enhance ChatGPT’s capabilities and function as OpenAI’s frontrunning model in the coming times. Presently, its access remains limited to paying developers with API access; however, access will be extended to Enterprise and ChatGPT Plus customers shortly. On the other hand, Google Gemini has three distinct models, with the Nano variant being built specifically for powering handheld devices like Google’s Pixel 8. The Pro model powers the current, updated version of Google Bard, while the yet-to-be-released Ultra variant will be used for Google Bard Advanced. Both GPT-4 Turbo and Google Gemini are highly efficient and perform much better than their predecessor models. The two also rank highly on several benchmarks, with comparable results on many of them.
The Prospects for AI Chatbots from Google and OpenAI
A growing AI market indicates more potential players in the future.
Both ChatGPT and Google Bard are bound to improve significantly following their switch to GPT-4 Turbo and Google Gemini, respectively. These developments also denote growing professional and corporate interest in language models, since the optimization of workflows and enhanced productivity has been of significant importance to these user groups. That being said, concerns over hallucination as well as AI bias remain, making adherence to responsible AI practices all the more necessary to aid the sustainable growth of artificial intelligence and machine learning in the long term.
FAQs
1. When were GPT-4 Turbo and Google Gemini launched?
While GPT-4 Turbo was launched on November 6, 2023, Google Gemini’s availability was announced by its parent firm on December 6, 2023.
2. Is Google Gemini better than GPT-4 Turbo?
While Google Gemini has an impressive score on the MMLU benchmark test, it is touted that GPT-4 Turbo is possibly better when it comes to aspects such as reasoning and mathematical capabilities.
3. Are GPT-4 Turbo and Google Gemini free?
No, GPT-4 Turbo is available only to paying developers presently, with access being extended to Enterprise and ChatGPT Plus customers shortly. On the other hand, Gemini Nano will be available exclusively to handheld device users such as those of Pixel 8, while its Pro version powers the regular version of Bard. Since Ultra is awaiting launch, it should be available only in the early months of 2024 to paid customers.