GPT 3 vs. GPT 4: Differences Between ChatGPT Models
When it comes to AI content generation, not all models perform the same. And this became clear to me when I started testing both GPT 3 and GPT 4 to select the right language model for GetGenie.
I ran a series of hands-on tests using both models inside OpenAI Playground. My goal was to evaluate how they perform across different GetGenie AI content templates, including blog posts, FAQs, and copywriting.
What I found interesting was that each had its own strengths. Based on output quality, consistency, and usability, I ended up selecting GPT-3 for certain templates and GPT-4 for others.
In this blog post, I’ll walk you through the exact metrics I used to test and compare both models. So, it’s GPT 3 vs. GPT 4.
Choosing between GPT-3 and GPT-4 isn’t about picking the “better” model—it’s about choosing the right one for the job. Both models shine in different scenarios depending on complexity, scale, and content goals.
This overview highlights their key differences so you can quickly decide which model fits your workflow best.
1. GPT-3 is ideal for fast, bulk content generation, while GPT-4 excels in complex, high-quality, and context-heavy tasks
2. GPT-3 delivers decent outputs but may lack depth, whereas GPT-4 provides more accurate, logical, and nuanced responses
3. GPT-3 handles text-only inputs, while GPT-4 supports multimodal inputs (text + images)
4. GPT-3 can generate creative content at scale, but GPT-4 produces more refined, human-like, and polished writing
5. GPT-3 is faster and more cost-efficient, while GPT-4 is comparatively slower but offers higher-quality output
6. GPT-3 works well for repetitive or template-based tasks, while GPT-4 is better for strategic, analytical, and detailed content creation
Ejemplo
Imagine you’re working on GetGenie templates. For generating multiple FAQs or short-form copies, GPT-3 can handle the volume efficiently.
But for long-form blog posts, in-depth comparisons, or content requiring strong reasoning, GPT-4 will deliver more structured, accurate, and engaging results.
GPT model comparison
GPT (Generative Pre-trained Transformer) is an AI language model that uses deep neural networks to generate human-like text. GPT helps in writing, translation, question-answering, image generation, coding, etc. Abierto AI has developed and trained this popular model with a large dataset of text and code.
¿Qué es GPT-3?
GPT-3, released May 28, 2020, was trained on a dataset of 500 TB of text and code. So, GPT-3 became very powerful and could generate text that resembled human-written text. The tool has amazed people with creative content and informative answers.
Later, developers presented GPT-3.5, an improved version of GPT-3. ChatGPT’s emergence is the result of GPT-3.5. Following this advancement, GPT-3.5 Turbo enhanced ChatGPT further.
¿Qué es GPT-4?
GPT-4 is the fourth model of OpenAI’s GPT series. GPT-4 was released in March 14, 2023. This model is a multimodal large language model, unlike GPT-3, which is unimodal. GPT-4 is more advanced and reliable than ever.
OpenAI has now made GPT-4 the main model for ChatGPT and is available with the free version.
GPT 3 frente a GPT 4: las diferencias
Though GPT-4 has already been released, it continues to evolve through updates and improvements. It has significantly transformed how we interact with computers, offering more accurate, nuanced, and context-aware responses than previous models. There are several core differences between GPT-3 and the latest GPT-4, including reasoning ability, language understanding, and multi-modal capabilities.
GPT-3 frente a GPT-4: tamaño del modelo
If you look at the GPT model sizes, you can see that OpenAI has trained them with really large datasets. But, How big is GPT-3? As per OpenAI, it has around 175 mil millones de parámetros. It was the largest language model available before GPT-4.
What about the number of parameters in GPT-4? It is estimated to be roughly around 1.80 trillion! This estimate first came from AI experts like George Hotz, who is also known for being the first person to crack the iPhone.
In case you are wondering what “parameters” actually represent, they are the internal weights the model learns during training. Think of them as the “knobs” or “settings” that the model adjusts to improve its ability to predict the next word in a sentence, understand meaning, follow instructions, etc. These are sometimes compared to neurons in the brain.
So, if you are asking the model size of GPT-4 as compared to GPT-3, GPT-4 model is over 10 times larger than GPT-3! Making it the smartest LLM to exist till date.
GPT-3 frente a GPT-4: qué se necesita y qué ofrece
GPT-3 acepta entrada de texto y usted puede realizar entradas de texto en cualquier idioma. Puede proporcionar indicaciones de texto, instrucciones, códigos, contenido extenso, etc., y solicitar resultados en consecuencia.
Differently, as per OpenAI, GPT-4 can handle about 24,000 words of text. However, the system understands inputs in multiple modalities and toma imágenes además de la entrada de texto. For some users, it can provide codes to build a simple website by taking only a hand-drawn mockup. Also, it can help you to recreate small games.
Users of ChatGPT Plus or Pro versions can develop their own GPTs or explore a myriad of GPTs integrated with other AI apps for various purposes. If you’re curious about how such AI models are built, check out this guide on creating an AI system from scratch.
Examples would be Canva for image creation or Capcut for AI video generation.
GPT-3 frente a GPT-4: límite de información
GPT-3 has information that has data up to September 2021. Any events, developments, or information after that date are not part of GPT-3’s training data. If you use the updated GPT-3.5 Turbo version, it has updated information up to December 2023.
GPT-4 “legacy version” has a knowledge cutoff up to September 2021. However, GPT-4 Turbo and and the newer GPT-4o (Omni) has broader general knowledge up to December 2023.
As per New York Post, GPT-4.5 is less prone to so-called “hallucinations” – a phenomenon where AI models fabricate false responses to user prompts. OpenAI said the upgraded model has a hallucination rate of just 37.1%, down from 61.8% from the last version. It’s built-in info is updated up to February 2025, the month of its preview release.
GPT-3 frente a GPT-4: calidad de salida
GPT-3 is a conversational tool and is good at generating content. The tool can create copies, long content, and answer questions. However, it lacks common sense and cannot think critically compared to GPT-4. Its “hallucination rate” is also much higher, providing inaccurate answers to simple tasks.
The output quality of GPT-4 is more accurate, collaborative, and advanced than the previous versions. It helps you to generate content, edit, and do repeated writing tasks smartly to lessen your pressure. GPT-4 can craft stories, lyrics, social media copies, long-form content, etc. based on the prompts. Also, the tool creates captions for images, does classifications, and analyses smoothly.
GPT-4o can also make summaries from audio files and read texts on images.
GPT-3 frente a GPT-4: comparación de usuarios
Muchas empresas modernas utilizan GPT-3 para desarrollar productos y servicios nuevos e innovadores. OpenAI utiliza GPT-3 para impulsar sus propios productos y servicios, como ChatGPT y DALL-E.2. Google utiliza GPT-3 para mejorar la precisión de sus resultados de búsqueda. Además, muchas herramientas populares de escritura de IA también funcionan con GPT-3. Por ejemplo, el servicio de chat Bing de Microsoft, el excelente generador de contenidos optimizado para SEO. GetGenie IA, Gramaticalmente, etc.
Por el contrario, aún se desconoce la lista de usuarios de GPT-4. Como el proceso de desarrollo aún está en marcha, la gente aún no puede utilizar ampliamente la herramienta. Sin embargo, OpenAI está utilizando GPT-4 para impulsar el nuevo servicio ChatGPT plus. Con suerte, DALL-E.3 también estará disponible para GPT-4 en el futuro y la gente podrá convertir ideas en imágenes fácilmente.
Sistema de precios
GPT-3 y GPT-3.5 son gratuitos. Puede utilizar ChatGPT gratuito en línea para generar contenido. Le brindará todas las actualizaciones periódicas del modelo sin comprar ningún plan.
GPT-4 cuesta $20 por persona al mes. Este plan le proporcionará análisis de datos avanzado, complementos, acceso temprano a funciones beta y los beneficios de la versión gratuita.
Una tabla de comparación rápida
| Características | GPT-3 | GPT-4 |
| Modalidad | Unimodal (solo texto) | Multimodal (texto e imágenes) |
| Exactitud | Menos precisa | Más preciso |
| Aplicaciones | Más de 300 aplicaciones | Desconocido, API disponible |
| Tamaño de los datos de entrenamiento de GPT | 175 mil millones de parámetros | 1.80 trillion parameters |
| Tamaño | 17 gigabytes | 45 gigabytes |
| Longitud del mensaje | 4.096 tokens (máximo) | 8,192 tokens (máximo) |
| Velocidad | 10 mil millones de tokens por segundo | 100 mil millones de tokens por segundo |
Preguntas frecuentes
Terminando
Entonces, desglosamos los detalles clave de GPT 3 frente a GPT 4. Espero que ahora tenga ideas claras sobre estos modelos de GPT.
Among modern businesses, writers, researchers, artists, and others, GPT has gained much popularity. Developers have already designed several writing assistants, chatbots, and other AI tools using GPT-3 and GPT-3.5. Now you can also look forward to seeing the magic of GPT-4.
Es importante tener en cuenta que GetGenie genera contenido para sus tareas de escritura aprovechando el modelo de lenguaje GPT de Open AI.
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