ChatGPT isn’t a monolith.
Since OpenAI first released the buzzy chatbot in 2022, it has rolled out what seems like a new model every few months, using a confusing panoply of names.
A number of OpenAI competitors have popular ChatGPT alternatives, like Claude, Gemini, and Grok. But OpenAI’s models are among the most recognizable in the industry and have attracted the most users. Some are good for quantitative tasks, like coding, while others are best for brainstorming new ideas.
Here is how ChatGPT has evolved, and how each model OpenAI has released is different.
GPT-5
In August, OpenAI released what it says is its most advanced model to date: GPT-5. OpenAI said the model marks “a significant leap in intelligence over all our previous models, featuring state-of-the-art performance across coding, math, writing, health, visual perception, and more.”
OpenAI CEO Sam Altman called it a “major upgrade” and “a significant step along the path of AGI” in a conference call with journalists the day before its release. He said that after using GPT-5, going back to GPT-4 was “miserable.”
GPT-5 has a “real-time router,” a system that automatically selects the most appropriate model to handle each user request, in place of the model chooser that was available in previous models.
The router was meant to simplify things for the user, but it has been met with backlash from users who developed strong attachments to its various AI models.
“If you have been following the GPT-5 rollout, one thing you might be noticing is how much of an attachment some people have to specific AI models,” Altman wrote on X. “It feels different and stronger than the kinds of attachment people have had to previous kinds of technology (and so suddenly deprecating old models that users depended on in their workflows was a mistake).”
So OpenAI brought back 4o, a fan favorite, and introduced more options for users to choose how ChatGPT does its work.
GPT-4 and GPT-4o
OpenAI first released GPT-4 in 2023 as its flagship large language model. Altman said in a podcast at the time that the model took “hundreds of people, almost all of OpenAI’s effort” to build.
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It then upgraded the model to GPT-4o, which it first released last year. It’s as intelligent as GPT-4, which is capable of acing the SAT, the GRE, and passing the bar — but is significantly faster and improves on its “capabilities across text, voice, and vision,” OpenAI says. The “o” stands for omni.
4o can quickly translate speech and help with basic linear algebra, and has the most advanced visual capabilities.
Its Studio Ghibli-style images drummed up excitement online. However, it also raised copyright questions as critics argued that OpenAI is unfairly profiting off artists’ content.
OpenAI says 4o “excels at everyday tasks,” such as brainstorming, summarizing, writing emails, and proofreading reports.
GPT-4.5
Altman described GPT-4.5 in a post on X as “the first model that feels like talking to a thoughtful person.”
It’s the latest advancement in OpenAI’s “unsupervised learning” paradigm, which focuses on scaling up models on “word knowledge, intuition, and reducing hallucinations,” OpenAI technical staff member Amelia Glaese said during its unveiling in February.
So, if you’re having a difficult conversation with a colleague, GPT-4.5 might help you reframe those conversations in a more professional and tactful tone.
OpenAI says GPT-4.5 is “ideal for creative tasks,” like collaborative projects and brainstorming.
o1 and o1-mini
OpenAI released a mini version of o1, its reasoning model, in September last year and the full version in December.
The company’s researchers said it’s the first model trained to “think” before it responds and is well-suited for quantitative tasks, hence the moniker “reasoning model.” That’s a function of its training technique, known as chain-of-thought, which encourages models to reason through problems by breaking them down step-by-step.
GPT-5 can now decide on its own how long it needs to think about something, and will choose o1 for complex tasks.
In a paper published on o1’s safety training, the company said that “training models to incorporate a chain of thought before answering has the potential to unlock substantial benefits, while also increasing potential risks that stem from heightened intelligence.”
In a video of an internal OpenAI presentation on the best use cases for o1, Joe Casson, a solutions engineer at OpenAI, demonstrated how o1-mini might prove useful to analyze the maximum profit in a covered call, a financial trading strategy. Casson also showed how the preview version of o1 could help someone reason through how to come up with an office expansion plan.
OpenAI says o1’s pro mode, a “version of o1 that uses more compute to think harder and provide even better answers to the hardest problems,” is best for complex reasoning, like creating an algorithm for financial forecasting using theoretical models or generating a multi-page research summary on emerging technologies.
o3 and o3-mini
Small models have been gaining traction in the industry for a while now as a faster and more cost-efficient alternative to larger, foundation models. OpenAI released its first small model, o3 mini, in January, just weeks after Chinese startup Butterfly Effect debuted DeepSeek’s R1, which shocked Silicon Valley — and the markets — with its affordable pricing.
OpenAI said 03 mini is the “most cost-efficient model” in its reasoning series. It’s meant to handle complex questions, and OpenAI said it’s particularly strong in science, math, and coding.
Julian Goldie, a social media influencer who focuses on SEO strategy, said in a post on Medium that o3 “shines in quick development tasks” and is ideal for basic programming tasks in HTML and CSS, simple JavaScript functions, and building quick prototypes. There’s also a “mini high” version of the model that he said is better for “complex coding and logic,” though it had a few control issues.
In April, OpenAI released a full version of o3, which it calls “our most powerful reasoning model that pushes the frontier across coding, math, science, visual perception, and more.”
OpenAI says o3 is best used for “complex or multi-step tasks,” such as strategic planning, extensive coding, and advanced math.
o4 mini
OpenAI released another smaller model, the O4 mini, in April. It said it is “optimized for fast, cost-efficient reasoning.”
The company said it achieves remarkable performance for cost, especially in “math, coding, and visual tasks.” It was the best-performing benchmarked model on the American Invitational Mathematics Examination in 2024 and 2025.
o4 mini, and its mini-high version, are great for fast and more straightforward reasoning. They’re good at speeding up any quantitative reasoning tasks you encounter during your day. If you’re looking for more in-depth work, opt for o3.
Scott Swingle, a DeepMind alum and founder of AI-powered developer tools company Abante AI, tested o4 with an Euler problem — a series of challenging computational problems released every week or so. He said in a post on X that o4 solved the problem in 2 minutes and 55 seconds, “far faster than any human solver. Only 15 people were able to solve it in under 30 minutes.”
OpenAI says the O4 mini is best used for “fast technical tasks,” like quick STEM-related queries. It says it’s also ideal for visual reasoning, like extracting key data points from a CSV file or providing a quick summary of a scientific article.
