In February 2024, the race between generative AI models took an interesting turn. 

With billions of dollars at stake, both OpenAI and Google’s primary aim has been to capture the market. After a year of dominance by OpenAI’sGPT-4, Google finally released its much-awaited Gemini Pro. But Google might have been too late with Gemini’s release.

Google’s generative AI project started out as Bard but quickly fizzled out due to a lack of consumer interest. In order to beat GPT-4, Google was required to come up with a more powerful all-purpose AI solution. The result was Gemini Pro.

What followed was an initial success through benchmark comparisons, but slowly turned into a PR disaster as Google’s Gemini Pro was blamed for displaying inaccurate information. 

Despite the backlash, Gemini Pro continues to hold interest among the generative AI community.

But how well does it fare against GPT-4? What can Gemini Pro do that GPT-4 cannot? 

Let’s take a deep dive into the Gemini Pro vs GPT-4 debate and find out who comes on top.

 

Table of Content

  1. Gemini Pro vs GPT-4: Understanding the Differences
  2. Gemini Pro vs GPT-4: Use Cases and Applications
  3. Gemini 1.5 Pro vs GPT-4: Benchmark Showdown
  4. Gemini Pro vs GPT-4: Capabilities and Performance
  5. Gemini Pro vs GPT-4: Comparison Summary
  6. Gemini Pro vs GPT-4: Which One is Right for You?
  7. Kanerika: Your Partner in AI Implementation
  8. FAQs

 

Gemini Pro vs GPT-4: Understanding the Differences

Google’s Gemini Pro and GPT-4 are both large language models (LLMs). They are algorithms trained on massive amounts of data to produce high-quality text, translate languages, write code, etc.

Let’s understand the key differences between them and where their specialties lie:

 

Gemini Pro Model: Multimodal & Expansive

 

Gemini Pro vs GPT-4 - Key Differences in use cases

 

Gemini Pro is the most recent large language model (LLM) released by Google AI, known for its versatility and efficiency. It follows Gemini 1.0 and is far superior to its predecessor.

Also Read- Google Gemini AI: Your Superpowered AI Assistant for the Future

Key Features of Gemini Pro:

  • Context Length: It can handle an impressive context length of 1 million tokens, surpassing GPT-4 Turbo’s 128K and Claude 2.1’s 200K token context lengths.
  • Multimodal Capability: Gemini Pro natively supports multimodal inputs, allowing it to process videos, images, and various file formats seamlessly.
  • Advanced Reasoning: In logical reasoning tests, Gemini Pro has shown improvement over its predecessors, correctly answering questions that previously stumped it.
  • Retrieval Capability: Google internally tested Gemini Pro with up to 10 million tokens, demonstrating its robust retrieval capability.

 

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GPT-4: The Established Contender in AI

Developed by OpenAI and released in 2023, GPT-4 is a prominent large language model (LLM) known for its diverse capabilities. While it shares some functionalities with Gemini Pro, it exhibits distinct strengths and areas of expertise.

 

Key Features of GPT-4:

  • Text Generation: Excels in generating different text formats. GPT-4 often displays a more detailed and user-prompt driven approach as compared to Gemini Pro.
  • Multilingual Communication: Understands and translates text across numerous languages, similar to Gemini Pro.
  • Code Generation: Demonstrates a slight edge in generating complex and intricate code formats. This has huge appeal to developers seeking assistance with challenging coding tasks.
  • Question Answering: Provides comprehensive and informative answers to user queries, similar to Gemini Pro. However, GPT-4 is claimed to be more accurate than Gemini Pro in this field.

 

While both Gemini Pro and GPT-4 have remarkable features, it’s important to remember that no generative AI model is perfect. They’re still in early development, similar to the original iPhone versus the Samsung Omnia Windows phone.

 

Gemini Pro vs GPT-4: Use Cases and Applications

Moving on to specific use cases, let’s explore how each model excels in different domains. Both models are adept at text generation, translation, and question-answering. Some anecdotal evidence suggests Gemini Pro demonstrates a slight edge in reasoning.

 

Gemini Pro Use Cases

 

Google's Gemini Pro has various use cases

Gemini Pro has captured the interest of the AI community, that hopes its performance can be better than the existing models

 

Gemini is constantly evolving. While it may not have made as large an impact as GPT-4, Gemini Pro is great at:

 

  • Generating human-friendly content: Gemini Pro offers a wide range of applications, including generating reports, articles, and blog posts with its strong grasp of factual language. Its proficiency in understanding information allows it to produce accurate and informative content across different fields.

 

  • Research and administrative tasks: Gemini Pro proves valuable in research assistance tasks such as analyzing large datasets, summarizing research papers, and extracting essential information. Moreover, businesses can leverage Gemini Pro for translation and localization purposes. It is also proficient at translating content for various audiences or creating localized marketing materials tailored for international markets.

 

  • Business intelligence and analysis: The LLM offers a suite of functionalities to support informed decision-making. Gemini Pro excels in market research and analysis by processing large volumes of data, enabling businesses to identify emerging trends and patterns.

 

GPT-4 Use Cases

 

opened-ai-chat-laptop (1)

GPT-4’s success lies in its ability to perform a wide range of tasks with minimal human intervention

 

GPT-4’s primary advantage lies in its plugins and API. Developers are familiar with its capabilities and adept at customizing the large language model (LLM) to suit specific needs. It can browse the web and offer recent information, while Gemini Pro, till now, has had to depend on training data.

 

  • Creative content generation: GPT-4 has diverse applications across marketing, storytelling, and product design. It allows users to generate engaging marketing copy, captivating ad content, and innovative marketing campaigns.

 

  • Software coding: GPT-4 acts as an indispensable tool. It assists developers by generating various types of code and identifying potential issues in existing code. Moreover, developers can utilize GPT-4 to brainstorm new coding approaches and experiment with innovative frameworks. GPT-4 automates the generation of documentation and comments within code, enhancing readability and maintainability.

 

  • CustomGPT is a powerful service that allows you to build your own ChatGPT chatbot tailored specifically to your business needs. It empowers businesses to provide accurate interactions while leveraging their own content. CustomGPT provides accurate answers without hallucinations, ensuring brand integrity. You can embed CustomGPT on your website, integrate it into workflows via API, or sell it using your pricing models.

 

Remember, this is not an exhaustive list, and both models can be applied creatively across various domains. 

 

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Gemini 1.5 Pro vs GPT-4: Benchmark Showdown

In evaluating the capabilities of AI models, particularly large language models (LLMs), benchmarks play a crucial role. Like grading systems used for humans, benchmarks serve as rigorous tests that push these models to their limits.

Thus, the question arises: How does Gemini stack up against GPT-4 in the realm of AI benchmarks?

This table provides comparisons between Gemini Ultra, Gemini Pro, GPT-4, and GPT-3.5 across a range of benchmarks.

 

Benchmark Gemini Ultra Gemini Pro GPT-4 GPT-3.5
MMLU 90.04% 79.13% 87.29% 70%
GSM8K 94.4% 86.5% 92.0% 57.1%
MATH 53.2% 32.6% 52.9% 34.1%
BIG-Bench-Hard 8 3.6% 75.0% 83.1% 66.6%
HumanEval 74.4% 67.7% 67.0% 48.1%
Natural2Code 74.9% 69.6% 73.9% 62.3%
DROP 82.4 74.1 80.9 64.1
Hellaswag 87.8% 84.7% 95.3% 85.5%
WMT23 74.4 71.7 73.8

 

Here’s a simplified interpretation of the table:

  • MMLU: Measures how well the models understand and respond to different language tasks. GPT-4 scored the highest (among LLMs available today for deployment). 
  • GSM8K: Evaluates their ability to solve grade-school level math problems. Again, GPT-4 performed the best.
  • MATH: Tests their math skills. GPT-4 and Gemini Ultra performed similarly here.
  • BIG-Bench-Hard: Challenges them with tough language understanding and reasoning tasks. All models did quite well.
  • HumanEval: Measures how closely their text resembles human responses. GPT-4 scored the highest.
  • Natural2Code: Checks their ability to turn human instructions into code. GPT-4 performed the best.
  • DROP: Assesses their ability to answer questions based on text passages. GPT-4 did the best.
  • Hellaswag: Tests their common sense and ability to predict outcomes. GPT-4 scored highest.
  • WMT23: This one likely tests translation accuracy between languages. All models performed similarly except GPT-4, which wasn’t tested.

 

Please note:

  • These are general figures based on publicly available information and may not represent the true performance of each model.
  • Different benchmarks measure different aspects of language model performance. It’s important to consider the specific task at hand when evaluating performance. One might be better at writing screenplays and the other at translating entire websites.
  • Language models are constantly evolving, so these benchmarks may not be completely accurate.

 

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Gemini Pro vs GPT-4: Capabilities and Performance

There are several other factors to be taken into consideration when discussing Gemini AI vs ChatGPT.

These are not purely related to AI (that is, how intelligent the model appears) but nevertheless affect end-user performance.

 

Context Length

Gemini Pro: Can handle a massive context length of 1 million tokens. This surpasses GPT-4 Turbo’s 128K and Claude 2.1’s 200K token context lengths. However, Google has stated that the public release model can handle only 128,000 tokens.

GPT-4: Has a context window of 128K tokens by default.

 

Multimodal Capability

Gemini Pro: Natively supports multimodal inputs, including text and images.

GPT-4: Primarily focuses on text-based inputs.

 

Retrieval Capability

Gemini Pro: Tested internally with up to 10 million tokens, showcasing robust retrieval capability.

GPT-4: Does not have the same tested retrieval capacity. The past year has shown it forgets information quite quickly.

 

Is Gemini better than ChatGPT? It entirely depends on your use case.

Gemini Pro exhibits exceptional multimodality. This allows it to process and comprehend various data types, such as text, images, audio, and video, simultaneously. 

This feature is favorable for tasks requiring a detailed understanding of mixed data, such as analyzing and generating multimedia content.

In contrast, GPT-4 demonstrates remarkable proficiency in language-related tasks. It excels in tasks requiring in-depth textual analysis, intricate language comprehension, and creative text generation. 

Its strength lies in its capacity to manage complex language structures and sustain context in extensive conversations. This makes it suitable for applications like conversational AI, content creation, and detailed text summarization.

 

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Gemini Pro vs GPT-4: Comparison Summary

Here’s a summary of the key differences and comparisons between Gemini Pro and GPT-4, including token size, parameters, and cost: 

 

Feature/Aspect Gemini Pro GPT-4
Developer Google DeepMind OpenAI
Token Size Gemini 1.5 Pro is noted for its 1M token context window. The GPT-4 model offers a context window of 8,000 tokens by default, with an extended version supporting up to 32,000 tokens.
Parameters Specific details on the number of parameters for Gemini Pro are not readily available. However, it’s part of Google’s large-scale AI models. GPT-4 is rumored to have around 1.76 trillion parameters, making it one of the largest models in terms of parameter count.
Cost Gemini Pro text output costs $0.000375 per 1,000 characters. Text prompt to image is priced at $0.020 per image. Since it is multimodal there is a huge price list for different tasks.  The cost for using GPT-4 varies based on usage and access method, with OpenAI offering different pricing tiers for API access. Text only prompts cost $0.03 per 1,000 tokens.
Multimodal Capabilities Strong in processing multiple data types (text, images, audio, video) simultaneously. Primarily focused on text, with advanced language understanding and generation capabilities.
Application Areas Ideal for multimodal tasks and applications requiring holistic data analysis. Best suited for conversational AI, content creation, and detailed text summarization.

 

Gemini Pro vs GPT-4: Which One is Right for You?

As things stand currently, GPT-4 would be the most ideal generative AI tool for both businesses and individuals. This is despite the fact that GPT-4 is known to regularly hallucinate and is quite slow with responses. But why does GPT-4 win over Gemini Pro?

This is because, while Gemini Pro and Gemini Ultra seem to have superior benchmarks and numbers on paper, their user interaction and accuracy of information have been poor. 

This has been largely attributed to Google’s miscalculated launch, which saw them push Gemini months before the original release date due to the rising popularity of GPT-4.

This is despite Google having a head start of many years over OpenAI – with Google having published numerous papers on AI models.

Does this mean Gemini is as good as gone?

Hardly. We can expect Google to bounce back strongly from this, and push a more calibrated version of Gemini into the market in the upcoming months. 

Other than the user-reported mishaps, Gemini Pro seems to be a creative tool that could seriously compete against GPT-4, provided it can get its accuracy and performance right.

But for now, the debate between Gemini Pro vs GPT-4 can be closed with a definite winner; GPT-4 seems to be a better tool by a wide margin.

 

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Kanerika: Your Partner in AI Implementation

At Kanerika, we pride ourselves on being more than just a service provider; we are your strategic partner in generative AI implementation

From initial consultation to deployment and ongoing support, Kanerika’s team of experienced AI professionals ensures your AI journey is always customized as per your requirements.

Let Kanerika be the catalyst for your AI transformation, and take the first step towards harnessing the power of AI to drive your business forward.

 

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FAQs

Is Gemini better than ChatGPT-4?

Gemini and ChatGPT-4 serve different purposes. Gemini may refer to a specific software or platform, that could be better for specific tasks, whereas ChatGPT-4 is a language model known for its advanced conversational abilities. The choice depends on your specific needs.

Is Gemini Advanced better than GPT-4?

Similar to the previous question, the comparison depends on the context and specific use cases. Gemini Advanced, if it refers to an advanced version of a specific software, might have features that are more suited for certain tasks compared to GPT-4, which excels in language processing.

How much is Gemini vs GPT-4?

The cost of Gemini and GPT-4 can vary greatly depending on the service provider, usage, and licensing agreements. It's best to check with the respective service providers for the most accurate pricing information.

Is GPT-4 the best AI?

GPT-4 is among the most advanced AI language models available, known for its wide-ranging capabilities in understanding and generating human-like text. However, "best" can be subjective and depends on the specific requirements of the task at hand.

Is paying for GPT-4 worth it?

Whether paying for GPT-4 is worth it depends on your use case. If you require advanced natural language processing capabilities, GPT-4 can be a valuable investment. Assess your specific needs and potential return on investment.

Can I use GPT-4 for free?

As of my last update, OpenAI provided limited free access to GPT-4 through various interfaces, but comprehensive or commercial use typically requires a subscription or payment.

How much is GPT-4 per month?

The monthly cost for GPT-4 depends on the usage, such as the number of tokens processed. OpenAI often has a pricing model based on usage. For current pricing, it's best to consult OpenAI's official website or contact them directly.

Is the Gemini app worth it?

The value of the Gemini app depends on its features and how well they align with your needs. It's advisable to review its functionalities, user reviews, and compare it with other similar apps to determine its worth for you.

Is Gemini a good platform?

The quality of the Gemini platform can be determined by its performance, user satisfaction, and how well it meets your requirements. Consider looking at user reviews and case studies for a comprehensive evaluation.

What is better than GPT-4?

"Better" is subjective and depends on the specific application. There may be other AI models or tools more suited for certain tasks, but as of my last update, GPT-4 is among the most advanced in terms of general language processing.