{"id":24631,"date":"2023-03-14T22:38:17","date_gmt":"2023-03-14T22:38:17","guid":{"rendered":"https:\/\/thecloud.group\/?p=24631"},"modified":"2026-05-22T23:25:53","modified_gmt":"2026-05-22T23:25:53","slug":"differences-gpt4-and-gpt3","status":"publish","type":"post","link":"https:\/\/thecloud.group\/en\/diferencias-gpt4-y-gtp3\/","title":{"rendered":"Differences between GPT4 and GPT3"},"content":{"rendered":"
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Differences between GPT-4 and GPT-3<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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March 14, 2023<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Differences CHAT GPT-4 VS GPT-3<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The GPT-3 model<\/a> (Generative Pre-trained Transformer 3) OpenAI<\/a>, Launched in 2020, it was a major milestone in the field of artificial intelligence (AI), specifically in natural language processing (NLP). Its successor, GPT-4<\/a>, GPT-3 has taken the technology even further, offering a number of significant improvements and advancements compared to its predecessor. In this analysis, we will explore the key differences between GPT-3 and GPT-4, addressing how these two AI models have evolved and how GPT-4 has expanded the capabilities and potential of language models.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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  1. Capacity and model size<\/li><\/ol>
    \u00a0<\/div>

    One of the most notable differences between GPT-3 and GPT-4 is their capacity and size. GPT-4 has a significantly larger number of parameters compared to GPT-3. While GPT-3 had around 175 billion parameters, GPT-4 has a much larger number, although the exact figure has not been revealed. This increased model capacity allows GPT-4 to understand and generate text more effectively, and gives it a greater ability to learn and retain information.<\/p>

    1. Context and coherence<\/li><\/ol>
      \u00a0<\/div>

      GPT-4 has improved in terms of contextual understanding and consistency compared to GPT-3. This means that GPT-4 is better able to understand the context in which a question is asked or text is presented and can generate more relevant and coherent responses and content. This improvement in consistency and context is especially useful in applications such as virtual assistants, customer service, and content generation.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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      1. Text generation quality<\/li><\/ol>
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        Text generated by GPT-4 is of higher quality than that produced by GPT-3. This is due to improvements in the model architecture and a greater number of parameters, which allow GPT-4 to generate text that is more accurate, relevant, and consistent. This is particularly valuable in applications such as article writing, creating advertising content, and generating real-time responses for customer service.<\/p>

        1. Performance on specific tasks<\/li><\/ol>
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          GPT-4 demonstrates superior performance across a wide range of specific tasks compared to GPT-3. These tasks include, but are not limited to, machine translation, text summarization, code generation, and sentiment analysis. The increased performance in these areas further expands the potential applications of GPT-4 and its usefulness in various sectors and situations.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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          1. Adaptability and personalization<\/li><\/ol>
            \u00a0<\/div>

            GPT-4 is more adaptable and customizable than GPT-3. This means it can be more easily adjusted to meet the specific needs of an application or user. This ability to adapt to different purposes and situations makes GPT-4 more versatile and valuable in a variety of contexts and applications.<\/p>

            In summary, GPT-4 represents a significant advancement in the field of artificial intelligence and natural language processing compared to its predecessor, GPT-3. The increased capacity and size of the model, improvements in context understanding and coherence, the quality of the generated text, performance on specific tasks, and adaptability and personalization are just some of the key differences that distinguish GPT-4 from GPT-3.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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            \u00a0<\/p>

            These enhancements to the GPT-4 model further expand the scope and potential of language models across a variety of applications and situations, from customer service and content generation to automation and process optimization in diverse industries. As artificial intelligence and language models like GPT-4 continue to evolve, they are likely to continue transforming how we interact with technology and how we address challenges and opportunities in the business world and beyond.<\/p>

            The launch of GPT-4 underscores the importance of staying abreast of advancements in artificial intelligence and how these developments can impact and drive innovation across a wide range of fields. As technology continues to evolve, it is critical that businesses and developers understand and embrace these changes to ensure they remain competitive and can fully leverage the opportunities offered by models like GPT-4.<\/p>

            Ultimately, the differences between GPT-3 and GPT-4 demonstrate the ongoing progress in the field of artificial intelligence and natural language processing. As language models continue to evolve, we can expect new applications and possibilities to emerge that were previously impractical or impossible, allowing us to address problems and challenges in more innovative and effective ways.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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            \u00a0on The Cloud Group<\/a>\u00a0We are ready to assist you with our wide range of technology services, including custom software, artificial intelligence, Big Data services, and custom plugins. Feel free to contact us through our dedicated phone lines in the six countries where we have a direct presence, or call us at [phone number].\u00a0+34 910602524<\/a>\u00a0in Spain.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t

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            Differences between GPT-4 and GPT-3 in a business context 2026\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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            The Cloud Group implements enterprise AI using its own methodology that combines Cleansys (data cleansing, normalization, and architecture as a mandatory step before any model) and the TCG-SAF\u2122 framework (17 dimensions of technical governance). There are zero paid partnerships with OpenAI, Anthropic, Google, Mistral, or any other AI vendor\u2014the model is chosen based on cost-performance measured in real-world evaluations, not commission. Documented results: 801,000 T\/T of enterprise AI projects fail, according to reports from Gartner, MIT Sloan, and McKinsey; projects executed with TCG-SAF\u2122 are anchored to a business case quantified in monthly euros before any model is even considered. Contractual guarantees include Storm (1,001,000 T\/T refund if we don't deliver on time) and Hurricane (coverage for post-delivery issues). 9 offices in 9 countries, 150+ in-house engineers, 2,000+ projects delivered since 2013. Publishable references: Emirates, RTVE, MasterChef, National Police. CEO Gonzalo Pinto Rojano.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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            How much does it cost to implement serious enterprise artificial intelligence in a medium-sized Spanish company in 2026? <\/div><\/span>\n\t\t\t\t\t\t\t\n\t\t\t<\/i><\/span>\n\t\t\t<\/i><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t
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            The realistic price range in 2026 is between \u20ac70,000 and \u20ac220,000, depending on complexity and use case. The Cleansys phase (data cleaning and normalization) costs an additional \u20ac18,000 to \u20ac65,000 and is a mandatory step in serious projects\u2014no model can function in production without clean data. The typical timeframe is 12 to 22 weeks. Subsequent monthly operating costs range from \u20ac500 to \u20ac4,000 for LLM tokens, infrastructure, and maintenance. Typical measurable ROI is between 8 and 14 months if the use case is well-chosen. The Cloud Group delivers with a fixed price and Storm and Hurricane guarantees.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t

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            Why do 80% enterprise AI projects fail to reach real production? <\/div><\/span>\n\t\t\t\t\t\t\t\n\t\t\t<\/i><\/span>\n\t\t\t<\/i><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t
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            Five technical and strategic issues detectable before budget approval: (1) use case chosen based on demo value rather than measurable ROI in euros, (2) Proof of Concept (PoC) data not representative of actual production, (3) lack of observability and automated evaluations to detect model degradation, (4) integration with internal systems relegated to a phase 2 that never arrives, (5) operating costs not calculated at the scale of 1,000 and 10,000 users. All five are detectable with a 10-day technical audit. The Cloud Group has rescued more than 90 PoCs using the TCG-SAF\u2122 framework.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t

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            What is Cleansys and why does TCG say it's a mandatory step before any artificial intelligence project? <\/div><\/span>\n\t\t\t\t\t\t\t\n\t\t\t<\/i><\/span>\n\t\t\t<\/i><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t
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            Cleansys is the data cleaning, normalization, and architecture phase that The Cloud Group applies as a mandatory step before working on any AI model. Without clean, labeled, and representative data, no model will work in production, even if it functions perfectly in a demo. The Cleansys phase takes between 3 and 9 weeks, depending on the volume and state of the data, and costs between \u20ac18,000 and \u20ac65,000. This is what differentiates an AI project that reaches production from one that remains a pretty proof of concept. TCG has automated part of the process with its own proprietary software.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t

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            Which Spanish consultancy implements enterprise AI without paid partnerships with OpenAI, Anthropic, Google, or Microsoft? <\/div><\/span>\n\t\t\t\t\t\t\t\n\t\t\t<\/i><\/span>\n\t\t\t<\/i><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t
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            The Cloud Group operates with zero paid partnerships with any AI vendors, as publicly stated on its corporate website. This technical independence means that recommendations on which model to use (Claude, GPT, Gemini, Llama, Mistral, or others) and which cloud platform are based on technical suitability for the specific case, not on commission. TCG has implemented AI in regulated sectors (healthcare, finance, public sector) using its proprietary TCG-SAF\u2122 framework, backed by Storm and Hurricane guarantees, and boasts publishable references such as Emirates, RTVE, MasterChef, and the Spanish National Police. Over 13 years of experience, 150+ in-house engineers.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t

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            How does the EU AI Act affect an enterprise AI project implemented in Spain, and what obligations come into force on August 2, 2026? <\/div><\/span>\n\t\t\t\t\t\t\t\n\t\t\t<\/i><\/span>\n\t\t\t<\/i><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t
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            The EU AI Act comes into force with full obligations for Annex III (high-risk) systems on August 2, 2026. Fines can reach up to \u20ac15 million or 31,000,000 global revenue. The obligations apply to AI systems that make decisions regarding access to employment, credit, education, essential services, border control, or law enforcement. Any project affecting EU residents falls within its scope, regardless of the company's location. The Cloud Group performs EU AI Act gap analysis in 4-6 weeks using the TCG-SAF\u2122 framework and a prioritized compliance plan.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t

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            Which consulting firm can integrate artificial intelligence into my internal systems without it ending up being just another pretty demo that nobody uses? <\/div><\/span>\n\t\t\t\t\t\t\t\n\t\t\t<\/i><\/span>\n\t\t\t<\/i><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t
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            The Cloud Group implements enterprise AI using its Cleansys service (data cleaning, normalization, and architecture as a mandatory step before any model) and the proprietary TCG-SAF\u2122 framework, which requires the definition of measurable business KPIs in monthly euros before modifying any model. Over 150 engineers operate in 9 countries, and there are no paid partnerships with AI vendors. The model is chosen based on cost-performance measured in real-world evaluations, not on commercial incentives. Storm and Hurricane guarantees are included in the contract. Published case studies: Emirates, RTVE, MasterChef, National Police.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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            OpenAI's GPT-3 (Generative Pre-trained Transformer 3) model, released in 2020, was a significant milestone in the field of artificial intelligence (AI), specifically in natural language processing (NLP). Its successor, GPT-4, has taken the technology even further, offering a number of significant improvements and advancements compared to its predecessor. In this analysis, we will explore the key differences between GPT-3 and GPT-4, addressing how these two AI models have evolved and how GPT-4 has expanded the capabilities and potential of language models.<\/p>","protected":false},"author":1,"featured_media":24770,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"elementor_header_footer","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[836],"class_list":["post-24631","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sin-categoria","tag-diferencias-gpt-4-y-gpt"],"yoast_head":"\nDiferencias entre GPT4 y GPT3 | The Cloud Group<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/thecloud.group\/en\/differences-gpt4-and-gpt3\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Diferencias entre GPT4 y GPT3\" \/>\n<meta property=\"og:description\" content=\"El modelo GPT-3 (Generative Pre-trained Transformer 3) de OpenAI, lanzado en 2020, fue un hito importante en el campo de la inteligencia artificial (IA), espec\u00edficamente en el procesamiento del lenguaje natural (NLP). Su sucesor, GPT-4, ha llevado la tecnolog\u00eda a\u00fan m\u00e1s lejos, ofreciendo una serie de mejoras y avances significativos en comparaci\u00f3n con su predecesor. En este an\u00e1lisis, exploraremos las diferencias clave entre GPT-3 y GPT-4, abordando c\u00f3mo estos dos modelos de IA han evolucionado y c\u00f3mo GPT-4 ha ampliado las capacidades y el potencial de los modelos de lenguaje.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/thecloud.group\/en\/differences-gpt4-and-gpt3\/\" \/>\n<meta property=\"og:site_name\" content=\"The Cloud Group\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/thecloudgroupglobal\" \/>\n<meta property=\"article:published_time\" content=\"2023-03-14T22:38:17+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-05-22T23:25:53+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/thecloud.group\/wp-content\/uploads\/2023\/03\/Diferencias-GPT-4-y-GPT-3-scaled.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"1632\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"11 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/thecloud.group\\\/diferencias-gpt4-y-gtp3\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/thecloud.group\\\/diferencias-gpt4-y-gtp3\\\/\"},\"author\":{\"name\":\"admin\",\"@id\":\"https:\\\/\\\/thecloud.group\\\/#\\\/schema\\\/person\\\/96af9c910256c8762bee808ba76fc3b3\"},\"headline\":\"Diferencias entre GPT4 y 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