GPT-4 vs GPT-4 Turbo: an in-depth analysis of real-world performance

Introduction

In the rapidly evolving landscape of artificial intelligence (AI), OpenAI’s recent developments stand out, particularly GPT-4 and the now previewed GPT-4 Turbo. GPT-4 Turbo, available to paying customers since Tuesday, Nov. 7, promises significant improvements and new capabilities. These advanced models have the potential to dramatically change how companies and individuals interact with AI. In this article, we explore the differences between these two models, based on our direct experience and practical application in generating content and email responses.

GPT-4 vs GPT-4 Turbo: the core differences

OpenAI has made significant improvements with GPT-4 Turbo, including greater input capacity (16 times more than GPT-4), higher speed, lower cost and up-to-date data until April 2023. On paper, these improvements look spectacular and could be a gamechanger for companies using AI for large-scale content production or customer service.

Increased input limit in GPT-4 Turbo

A crucial improvement in GPT-4 Turbo is the significantly increased input limit, which is now up to 16 times larger than in previous versions. This development is invaluable for performing complex and detailed tasks. In particular, when responding to customer emails, we found that GPT-4’s input limit was often a limiting factor. A single e-mail, especially in cases of extensive correspondence, can already take up a substantial portion of the allowed input. In addition, questions on specific topics, such as the results of a Keyboost campaign, required detailed information and explanations about our portal, so the input limit was quickly reached.

With GPT-4, we were forced to strictly limit the amount of information we provided, which sometimes resulted in less detailed or less accurate answers. The introduction of GPT-4 Turbo eliminates this limitation, so we are now able to provide more extensive context and specific details. This ensures that GPT-4 Turbo should be better informed and therefore able to generate answers that are richer and more accurate.

Notable quality differences: GPT-4 vs GPT-4 Turbo in practice

Contrary to the expectation that GPT-4 Turbo would be at least equivalent to GPT-4 in terms of answer quality, practical scenarios show that this is not always the case. Even with identical question sets, GPT-4 Turbo sometimes produces inferior answers. For example, in the case of a customer with a domain name problem, GPT-4 correctly indicated that our hosting and domain name operations had been transferred to another party since July 1, 2023. GPT-4 Turbo, on the other hand, incorrectly suggested that we were in the process of resolving the problem. In another case, upon a report of double payment, GPT-4 offered a careful response focused on verifying and refunding the amount, while GPT-4 Turbo falsely promised an immediate refund. In addition, when requesting a quote, GPT-4 correctly guided the customer through the process, while GPT-4 Turbo caused confusion by providing instructions with links to be clicked over in a different language.

Interestingly, even when the ‘temperature’ setting is set to 0 – a setting that should result in consistent answers – GPT-4 Turbo does not always show the same reliability as GPT-4.

These examples illustrate that despite the advanced features of GPT-4 Turbo, GPT-4 remains a more reliable and accurate source of answers in certain complex situations.

Higher speed, lower price and up-to-date information in GPT-4 Turbo

While the increased speed of GPT-4 Turbo is a remarkable technical achievement, in our operation, where we create 20,000 blog articles monthly and process about 15,000 emails, it has not had a significant impact. The speed at which AI generates responses was already sufficient for our needs with previous versions. However, the main advantage for us lies in the more recent data available to GPT-4 Turbo. This timeliness is especially valuable when creating blog articles, as it increases the relevance and accuracy of the generated content.

Nevertheless, we must consider the cost trade-off. Although GPT-4 Turbo is superior to GPT-3.5 Turbo in some areas, particularly due to more recent data, price remains a major factor. GPT-4 Turbo is still about ten times more expensive than GPT-3.5 Turbo. This price difference is not negligible, especially considering the large volume of content we produce.

Conclusion

While GPT-4 Turbo promises impressive technological advances, in our experience the results are not always superior to GPT-4. It is important that companies thoroughly test these models in their specific context before making the final switch. AI technology is evolving rapidly, but practicality and accuracy remain critical to business success.

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