Choosing Your OpenAI ChatGPT Model A Practical Guide
OpenAI's ChatGPT comes in different forms. Here's a guide on which one is best to use and when. Image: Jaque Silva/NurPhoto
ChatGPT isn't a single, monolithic entity. Since OpenAI first launched the popular chatbot in 2022, it has introduced a series of new models, often with a bewildering array of names. Over the past few years, OpenAI has developed numerous models, including large language models like GPT-4 and GPT-4.5, as well as reasoning models like o1. This guide will help you understand what they do and how to use them effectively.
While many competitors offer ChatGPT alternatives such as Claude, Gemini, and Perplexity, OpenAI's models remain some of the most recognized in the AI industry. Some are tailored for quantitative tasks like coding, while others excel at brainstorming and creative endeavors. If you're seeking clarity on which model to use for specific purposes, this guide is for you.
Understanding GPT 4 and GPT 4o
OpenAI launched GPT-4 in 2023 as its premier large language model. CEO Sam Altman mentioned in an April podcast that building this model involved "hundreds of people, almost all of OpenAI's effort."
Subsequently, OpenAI upgraded its flagship model to GPT-4o, first released last year. GPT-4o matches the intelligence of GPT-4—which is capable of acing standardized tests like the SAT, the GRE, and passing the bar exam—but it is significantly faster and offers improved capabilities across text, voice, and vision. The "o" in GPT-4o stands for omni.
GPT-4o can quickly translate speech, assist with basic linear algebra, and possesses the most advanced visual capabilities among OpenAI's models. Its ability to generate Studio Ghibli-style images created considerable excitement online, though it also brought up copyright concerns, with critics arguing that OpenAI might be unfairly benefiting from artists' original content.
OpenAI states that GPT-4o "excels at everyday tasks," such as brainstorming, summarizing text, writing emails, and proofreading reports.
Exploring GPT 4 5 The Thoughtful AI
Sam Altman described GPT-4.5 in a post on X as "the first model that feels like talking to a thoughtful person."
This model represents the latest progress in OpenAI's "unsupervised learning" paradigm. Amelia Glaese, an OpenAI technical staff member, explained during its unveiling in February that this approach focuses on scaling up models based on "word knowledge, intuition, and reducing hallucinations."
Practically, if you're navigating a challenging conversation with a colleague, GPT-4.5 could help you rephrase your points in a more professional and tactful manner.
OpenAI suggests that GPT-4.5 is "ideal for creative tasks," including collaborative projects and brainstorming sessions.
The Reasoning Power of o1 and o1 mini
OpenAI released a mini version of o1, its reasoning model, in September of last year, followed by the full version in December.
Company researchers claim it's the first model trained to "think" before it responds. This capability stems from its training technique, known as chain-of-thought, which encourages the model to reason through problems by breaking them down step-by-step. Consequently, it is well-suited for quantitative tasks, earning it the title of a "reasoning model."
In a paper discussing the model's safety training, OpenAI noted 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."
During an internal OpenAI presentation, Joe Casson, a solutions engineer, demonstrated o1-mini's utility in analyzing maximum profit for a covered call, a financial trading strategy. Casson also showed how the preview version of o1 could assist in reasoning through an office expansion plan.
OpenAI indicates that 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 suited for complex reasoning. This includes tasks like creating an algorithm for financial forecasting using theoretical models or generating a multi-page research summary on emerging technologies.
Efficient Reasoning with o3 and o3 mini
Smaller models have been gaining popularity in the AI industry for some time as faster and more cost-efficient alternatives to larger foundation models. OpenAI launched its first small model, o3 mini, in January, just weeks after Chinese startup Butterfly Effect debuted DeepSeek's R1, which made waves in Silicon Valley and the markets with its affordable pricing.
OpenAI describes o3 mini as the "most cost-efficient model" in its reasoning series. It is designed to handle complex questions and is particularly strong in science, math, and coding.
Julian Goldie, a social media influencer specializing in SEO strategy, noted in a Medium post 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, which he found better for "complex coding and logic," albeit with 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 recommends using o3 for "complex or multi-step tasks," such as strategic planning, extensive coding projects, and advanced mathematics.
Fast and Cost Efficient o4 mini
OpenAI released another smaller model, the o4 mini, in April. The company stated it is "optimized for fast, cost-efficient reasoning."
According to OpenAI, o4 mini achieves remarkable performance for its cost, especially in "math, coding, and visual tasks." It was the best-performing benchmarked model on the American Invitational Mathematics Examination in both 2024 and 2025.
The o4 mini, along with its mini-high version, is excellent for rapid and more straightforward reasoning tasks. They can help speed up any quantitative reasoning work you encounter daily. However, if you require more in-depth analysis, o3 is the better option.
Scott Swingle, a DeepMind alumnus and founder of Abante AI, an AI-powered developer tools company, tested o4 mini with an Euler problem—a series of challenging computational problems. He reported in a post on X that o4 mini 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 suggests that the o4 mini is best utilized for "fast technical tasks," such as quick STEM-related queries. It's also described as ideal for visual reasoning, like extracting key data points from a CSV file or providing a quick summary of a scientific article.
