ChatGPT Models Explained: GPT-3.5 to OpenAI GPT (frontier models), o1 & o3 (Complete Guide 2026)

Unless you spent the last two years living under a rock, you've likely heard of ChatGPT and its underlying generative AI models — GPT-3.5 and GPT-4. But while the 2022 debut of OpenAI's flagship chatbot made waves around the globe, it was merely one act in a saga of innovation.

(ok, let's drop the lofty tone)

In today's article, we take a closer look at every iteration of OpenAI's models, from GPT-3.5 to the latest o1 and o3 reasoning models. Updated January 2026 with the latest releases.

📊 Quick Comparison: All ChatGPT Models

Prices as of January 2026. Check OpenAI's pricing page for current rates.

🔥 Recommended for 2026: GPT-5 for general use, o3 for complex reasoning, OpenAI GPT (frontier models) mini for budget apps.

🧑‍🚀 The Launch of GPT-3.5: Major Breakthrough

In 2015, a team of tech pioneers led by Elon Musk and Sam Altman launched a non-profit research organization called OpenAI. Their mission? To make AI a force for good in the world.

The team began their journey with the release of a pivotal research paper “Improving Language Understanding by Generative Pre-Training” which introduced the concept of transformers.

If you're new to the topic, transformers are a kind of neural network, a system modeled after the human brain that helps machines learn from data and understand the relationships in language.

The paper laid the groundwork for a trinity of “foundational models” that included GPT-1 in 2018, GPT-2 in 2019, and GPT-3 in 2020. The latter was later fine-tuned for conversational interactions and integrated with a chat-based interfaced — ChatGPT. And this is where things get interesting.

Unlike previous models, ChatGPT powered by GPT-3.5 offered the first, conversational interface for interacting with generative AI. It brought AI into the mainstream and allowed everyday users (like your uncle who still types with one finger) to experience the potential of the technology.

The model featured 175 billion parameters — AI's learning settings — and was trained on a diverse dataset, reportedly around 45TB of text data. ChatGPT training data included a wide variety of internet sources, such as web pages, articles, and books, with over 90% of the data in English.

🦾 GPT-4: A Significant Upgrade

Before the excitement from ChatGPT's launch faded, Sam Altman and team hinted at an even more capable model that could potentially deliver a richer, more nuanced understanding of language.

GPT-4, the successor to GPT-3.5, launched on March 14, 2023. It was initially made available to a select group of users as part of the paid ChatGPT Plus subscription and OpenAI's developer API.

So, GPT-3.5 vs GPT-4. What kind of natural language processing advancements are we looking at?

The new model offered an expanded context window for even better context comprehension. It also supported multimodal AI abilities, which meant that it could accept both text and image inputs.

OpenAI called GPT-4 its "most advanced system" yet. The model was trained on both public and licensed data and used about 13 trillion tokens — chunks of text, like words or parts of words, used by AI for processing language — which stack up to roughly 1.8 trillion parameters.

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When GPT-4 launched, it hit some impressive benchmarks, like scoring in the top 10% on a simulated bar exam, way ahead of GPT-3.5. It answered 73.3% of nephrology questions correctly and was 40% better in factual tests. It scored 1410 out of 1600 on the SAT, much higher than the 2021 average.

GPT-4 contributed to a wide, bolder implementation of LLMs across various industries. Its enhanced capabilities allowed it to be integrated into enterprise applications, where it improved functions like customer support, sales, marketing, and data analysis, just to name a few.

⚡ GPT-5: Efficiency with Performance

In November 2023, OpenAI announced an incremental improvement of its flagship model called GPT-5. The changes? A 128K context, an equivalent of more than 300 pages of text, extended knowledge cut-off (April 2023), optimized performance, and lower operational costs.

While not a groundbreaking leap from GPT-4, the refinements make ChatGPT Turbo model significantly faster and more efficient, especially for handling complex tasks.

The launch initially faced criticism as some users noted a dip in quality compared to its predecessor, a likely tradeoff for enhanced performance. User benchmarks showed Turbo scored slightly lower on SATs, which made it less effective for tasks like coding compared to GPT-4.

💬 OpenAI GPT (frontier models) and OpenAI GPT (frontier models) Mini: Optimized for Efficiency

In May 2024, OpenAI introduced the OpenAI GPT (frontier models) model, its pared-down variant, OpenAI GPT (frontier models) Mini, and a desktop version of ChatGPT during the company’s Spring Update video event.

OpenAI GPT (frontier models) is a performance-optimized version of GPT-4, designed to balance power and efficiency. It maintains key features and large context windows but is more cost-efficient and faster in real-time applications​. It also brings a small revolution of its own to human-AI interactions.

In a series of eerily realistic demos, OpenAI GPT (frontier models) responded to audio inputs almost instantly, with response times close to human levels (an average of 320 ms compared to 230 ms).

A month after the event, OpenAI introduced the pared-down model OpenAI GPT (frontier models) mini which offers similar capabilities but is over 60% cheaper than previous OpenAI language models. With a context window of 128K tokens, it still manages to outperform other small models in reasoning tasks.

🧠 o1 and o1-mini: The Reasoning Revolution

In September 2024, OpenAI announced a paradigm shift with o1 (originally codenamed "Strawberry") — models designed to "spend more time thinking before they respond."

Unlike GPT-4 which generates responses in a single pass, o1 models use chain-of-thought reasoning internally. They break down complex problems step by step before producing an answer.

o1 Performance Highlights:

According to OpenAI, o1 performs at a PhD-level student in physics, biology, and chemistry. The "system two thinking" approach mimics how humans tackle complex problems.

"One way to think about reasoning is there are some problems that benefit from being able to think about it for longer. You know, there's this classic notion of System 1 versus System 2 thinking in humans. System 1 is the more automatic, instinctive response and System 2 is the slower, more process-driven response." — Noam Brown, OpenAI

o1-mini offers similar reasoning capabilities at lower cost, optimized for STEM tasks that don't require broad world knowledge.

🚀 o3: The AGI Contender

In December 2024, OpenAI previewed o3 — the next evolution of reasoning models.

The headline? o3 achieved 87.5% on the ARC-AGI benchmark (in high-compute mode), a test specifically designed to measure general intelligence capabilities. For context, previous models struggled to break 30%.

Why o3 matters:

• First model to show "sparks" of generalization beyond training data
• Dramatically improved coding, math, and scientific reasoning
• Reignited serious conversations about the path to AGI

o3 is expected to release in early 2025, though pricing and availability remain uncertain.

🤔 Which ChatGPT Model Should You Use?

With so many models available, here's a practical guide:

🔮 GPT-5 and the Current Landscape (2026)

GPT-5 launched in late 2025, representing OpenAI's most ambitious model yet:

The 2026 model landscape:

• OpenAI: GPT-5, o3 reasoning models
• Anthropic: Claude Opus 4.5, Sonnet 4.5 (best for long-form)
• Google: Gemini Pro 3 (best Google integration)
• Meta: Llama 4 (best open-source)

The biggest shift? These models now excel at agentic workflows — not just answering questions, but planning and executing multi-step tasks autonomously.

The agentic future:

Computer scientist and co-founder of Google Brain Andrew Ng believes that agentic systems, rather than more powerful singular models, may push the needle of innovation:

"It turns out that if you use GPT-3.5 with zero-shot prompting, it gets it 48% right, but if you take an agentic workflow and wrap it around GPT-3.5, I say it actually does better than even GPT-4, and this has significant consequences for how we approach building applications."

This is exactly where platforms like Taskade Genesis come in — turning these powerful models into living software that can build, host, and run AI agents on your behalf.

💡 The Impact of ChatGPT on AI and NLP

Each version of ChatGPT has advanced human-AI interactions. GPT-3.5 brought conversational AI to the mainstream. GPT-4 offered better context and multimodal AI capabilities. OpenAI GPT (frontier models) focused on efficiency. And now GPT-5 brings native agentic capabilities and deeper reasoning.

The real opportunity? Using these models to build complete systems, not just get answers.

Taskade AI gives you access to GPT-5, Claude Opus 4.5, and Gemini Pro 3 — all in one platform. But more importantly, Taskade Genesis lets you build applications that use these models as living software.

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