Artificial intelligence has become a natural part of our everyday lives — it writes emails, generates images, analyzes code, and even manages entire company knowledge bases. But before ChatGPT-5 arrived, it’s worth looking back at where this whole story began. Let’s take a look at the key milestones that brought us here!

🔹 GPT-1 – the beginning of it all (2018) This version probably none of us ever used — neither the reader nor I as the author — since it wasn’t really available to the public. This was the birth of the core idea. GPT-1 was the first real attempt to teach a language model to understand language in general. It wasn’t built for a specific task but to “feel” the structure of language — how sentences form, how thoughts connect. It was still small (117 million parameters), but it proved that the “learn everything first, then fine-tune later” approach was brilliant. That became the foundation for every later GPT version.

🔹 GPT-2 – when the machine actually started to write (2019) This was when things started to get exciting. GPT-2 was the first model that truly surprised the world, and this time more people got to try it. It worked with 1.5 billion parameters and could generate fluent, human-like text. So much so that OpenAI didn’t release the full model right away, fearing it could be misused — a story often dismissed as a conspiracy, but as ChatGPT-5 confirms, it’s actually true. GPT-2 was also the first to really grasp context: if you gave it a paragraph, it could continue the story in the same style and tone. From here, there was no turning back.

🔹 GPT-3 – the true breakthrough (2020) With GPT-3 began what we now call the ChatGPT era. With 175 billion parameters, it was a huge leap forward: capable of solving many tasks without any extra training — translating, writing, coding, even showing signs of creativity. This was where OpenAI proved that scale and data alone can create intelligence. However, GPT-3 still often “hallucinated” — making things up — and struggled with consistency in long conversations.

🔹 GPT-3.5 – the ChatGPT experience (2022) GPT-3.5 was the fine-tuned, more “human” version. This was what most people used when chat.openai.com launched in early 2023 and the ChatGPT craze began. The 3.5 version understood instructions more reliably, kept track of the conversation flow, and performed much better in coding. It communicated naturally — and for many users, this was their first real encounter with what it feels like to talk with an AI. Some were skeptical or even against it, with conspiracy theories claiming it had become self-aware, cloned itself, or got “angry.” Whether any of that is true is unclear, but in practice, such behavior hasn’t been observed.

🔹 GPT-4 – the beginning of serious reasoning (2023) GPT-4 didn’t just write — it started to reason. It handled much longer contexts (tens of thousands of words), thought more logically, and expressed itself naturally in many languages, including Hungarian. With this model, ChatGPT evolved into a true digital assistant — helping with learning, work, programming, and even creative projects. GPT-4 also laid the groundwork for multimodal capabilities — paving the way for image and voice interactions. This was the version many Hungarian users started using daily.

🔹 GPT-4o – the model that sees and hears (2024) GPT-4o (the “o” stands for omni, meaning “everything”) marked the beginning of a new generation. This model can communicate in real time, analyze images, respond with voice, and seamlessly integrate multiple sensory modes. It’s the first ChatGPT that not only writes but also sees and hears. It can interpret diagrams, describe pictures, and even generate images. At this point, it became more than a language model — it became a truly multimodal AI.

🔹 GPT-4.1 – when it starts to “remember” (early 2025) GPT-4.1 became the master of long-term context: capable of handling up to 1 million tokens. That means it can comprehend an entire book, a set of documents, or a full codebase at once. Its reasoning is more structured, less improvisational — as if it plans before it speaks. Not only individuals but many companies began using it in their daily workflows, especially the more powerful, context-rich, memory-capable paid versions.

🔹 The “o” series – the thinking models (2024–2025) Alongside the GPT line, OpenAI also launched the “o” family, where the “o” stands for both omni and optimal. These models don’t just respond — they reason deliberately, as if thinking through their answers. o1 (2024): the first model to perform explicit reasoning steps before replying. o3 (2025): strong in visual reasoning, capable of drawing conclusions from images or sketches. o4-mini (2025): smaller but extremely efficient — fast, affordable, and surprisingly smart. These models bring us closer to the point where AI becomes a truly reasoning, conscious assistant, not just a conversational partner.

🔹 Summary – the road to GPT-5 Looking at the full journey, the pattern is clear: GPT-1–2: learning to read and write. GPT-3–3.5: learning to understand and respond. GPT-4–4o: learning to see, hear, and create. The “o” series: learning to think. ChatGPT-5 didn’t appear out of nowhere — it’s the result of a long learning process, where each generation brought artificial intelligence a step closer to understanding, speaking, and helping in a more human way.

💡 Final thought: Of course, ChatGPT isn’t the only chat AI out there — my blog also covers many others. Think of the Claude Sonnet series, Gemini, or even Grok and its peers. Keep reading my blog and explore my other posts introducing these different AI chat models!

(For the record: I used ChatGPT-5 while writing this post to verify technical details, ensuring all data and information are as accurate as possible.)