Lately, it feels like there’s a new ChatGPT version popping up every other day. There’s GPT-4o, the all-rounder, o3, the deep thinker, some speedy “mini” models that no one knows what they do, GPT-4.5 for creative writing, and a few legacy versions you probably would want to avoid. So if you’ve ever wondered which ChatGPT version to pick for your task- you are not alone! Even experts struggle to decide which ChatGPT version to use and when.
But a few days back Andrej Karpathy made his opinions clear! In this guide, I’ll walk you through Andrej Karpathy’s suggestions and preferences regarding each ChatGPT version so you can find the one that suits you best.
Table of contents
ChatGPT Versions
ChatGPT currently offers three different subscriptions, each with its own set of ChatGPT versions that you can access. Here is a breakdown of it:
| Type of Subscription | ChatGPT versions |
|---|---|
| Free | GPT‑4.1 mini (unlimited), GPT‑4o, o4-mini (limited) |
| Plus ($20/month) | GPT-4o, o3, o4-mini, o4-mini-high, GPT‑4.5, GPT‑4.1, GPT‑4.1-mini |
| Pro ($200/month) | GPT-4o, o3, o4-mini, o4-mini-high, GPT‑4.5, GPT‑4.1, GPT‑4.1-mini, o1 pro mode |
Most of these versions bring something unique and are specialized for different tasks. Using a single model for all of your tasks is a thing of the past when we didn’t have the options. Now it’s about using the right model for each task. But not all models are worth it and some of them are just to be ignored – at least that’s what is Andrej Karparthy’s opinion.
Let’s break down his assessment of all the ChatGPT versions.
Decoding ChaGPT Models with Andrej Karpathy
Andrej Karpathy is a well-known AI researcher known for his work in deep learning and computer vision. Last week he shared his thoughts on various LLMs that ChatGPT has to offer.
GPT-4o
“Use this model for anything easy and fast. It is great for general tasks”
– Andrej Karparthy
GPT-4o is the most reliable model under the ChatGPT hood. The model is designed to provide a balance between speed and accuracy. It handles a wide variety of tasks with great ease and coherence, making it ideal for most of our day-to-day tasks. Whether you need to whip up an email, write a blog post, or answer a general query, GPT-4o has your back.
Which tasks to use GPT-4o for?
- Writing emails, social media posts, and blogs
- Answering FAQs or general knowledge questions
- Light coding assistance like simple function generation or debugging
- Summarizing articles or documents
- Casual conversation and brainstorming
Where it struggles: It is less effective for deeply complex reasoning or tasks requiring multi-step logic and precision, where specialized models perform better.
My take: GPT-4o is the best default model for most users – fast, versatile, and reliable. It’s the go-to choice for everyday AI assistance.
o3
“Use this model for anything hard and important. The model is slow but super intelligent”
– Andrej Karparthy
Now, o3 is the “thinker” in the ChatGPT model family. This model is optimized for advanced reasoning and complex problem-solving. It trades speed for intelligence, giving detailed responses on tasks that require multi-step thinking or comprehensive analysis. So if you have a tricky document to review Or maybe just a difficult maths problem or equation, this model takes its time to dig deep and process hard and provide you with exact solutions.
Which tasks to use o3 for?
- Legal document analysis and contract review
- Complex scientific research and data analysis
- Debugging and explaining complicated code
- Writing detailed technical or academic reports
- Tasks requiring critical, step-by-step reasoning
Where it struggles: The model offers slower response times and higher compute requirements making it less suitable for quick, casual tasks or large-scale production environments where speed is critical.
My take: Use o3 when accuracy and depth matter more than speed. It’s the heavy hitter for tough, important problems.
o3 Pro
o3 Pro is the latest addition to the ChatGPT family. This version promises more computational power than its counterpart o3 with higher accuracy for complex queries. This version of ChatGPT comes with better tool integration and thus is capable of providing more relabible responses for web searches and file analysis. Compared to o3 it is slow, yet when pitied against other top reasoning mode, o3 Pro plays fast. So if you have a task that requires breaking down of complex tasks, in depth analysis of code or maths – the model can help but its recommended to validate its responses as the model largely feels like a hald baked cookie.
Which tasks to use o3 Pro for?
- Multi step code synthesis or Python execution
- Document summarization and audit compliance
- Image or document analysis
- Strategising long term business goals
- Searchhing across different online platforms
Where it struggles: The model struggles with accuracy and proper reasoning when dealing with multi-pronged problems.
My take: The model can be used for non-critical data analysis tasks or in areas where you want a quick response for a slightly difficult task.
Also Read: OpenAI o3 pro vs Gemini 2.5 pro
o4-mini
“Do not use this model”
– Andrej Karparthy
This model was launched to bring advanced reasoning at a really fast speed and that is exactly where things get tricky. The model can generate answers quickly but it tends to produce less reliable and mostly incoherent results. Its speed can be an advantage but it doesn’t outweigh the hallucinations and inaccuracy. All of this makes it unsuitable for professional or serious use.
Which tasks to use o4-mini for?
- Experimental projects where speed matters more than correctness like for vibe coding.
- Casual or non-critical testing and play like for designing children’s games.
Where it struggles: The model produces inconsistent, inaccurate, or incomplete answers, especially on technical or factual queries.
My take: Despite its speed, I will not recommend it due to poor reliability. It is better to choose a slower but more reliable model.
o4-mini-high
“Do not use this model”
– Andrej Karparthy
The model is a twin to o4-mini when it comes to performance. That is why similar to the o4-mini, the o4-mini-high model comes with speedy outputs with better coding and visual reasoning capabilities. However, this model too has the fundamental issues of poor reliability and quality. The speed comes at the cost of accuracy resulting in incorrect code suggestions or flawed reasoning. Unless you are testing experimental features casually, it is best to avoid this model for critical work.
Which tasks to use o4-mini-high for?
- Quick, rough coding or visual reasoning demos (e.g., showing a concept in a hackathon or workshop)
- AI experiments where speed trumps correctness (e.g., playful AI-based games or chatbots)
Where it struggles: The model offers lower output quality and reliability; prone to errors and hallucinations.
My take: I will not advise using this model for serious tasks, it’s only okay for casual playing.
o1 Pro Mode
“Do not use this model”
– Andrej Karparthy
o1 Pro is the grandfather for the reasoning models. Once considered an expert reasoning model, o1 Pro Mode is now largely outdated. The model available only in the Pro version, is largely inaccessible for many. It faces tough competition from many new models by Gemini and Deepseek that provide better results at a much lower cost. Although it can still produce thoughtful answers, its slower speed and outdated architecture make it less appealing for most current applications.
Which tasks to use o1 Pro for?
- Running legacy projects that require backward compatibility (e.g., maintaining older AI workflows)
- Not recommended for new or critical tasks
Where it struggles: Slower speed, lower accuracy compared to newer models, and missing the latest features.
My take: Its time to say goodbye and move on to better, faster options.
GPT-4.1
“Use this model for vibe coding”
– Andrej Karparthy
For the coders and techies, GPT-4.1 is a handy sidekick. The model is made for rapid and effective coding support. It is optimized to generate code snippets, debug scripts, and assist coders efficiently. It produces a great balance between speed and contextual understanding, enabling fast iteration during development. While it may not match o3’s reasoning depth, it provides practical coding help that is ideal for day-to-day programming tasks.
Which tasks to use GPT-4.1 for?
- Writing, debugging, or explaining code snippets
- Rapid prototyping during software development (e.g., generating boilerplate code)
- Learning programming concepts or getting quick code examples.
Where it struggles: In tasks involving complex or deeply analytical tasks outside coding.
My take: Great for developers who want swift, solid support on their coding journey.
GPT-4.1-mini
“Do not use this model”
– Andrej Karparthy
The mini version of GPT-4.1 promises speed but falls short on quality and coherence. It often produces poorer quality and less reliable outputs than its counterparts of similar sizes. Like other mini models, it’s better suited for experimentation or casual use rather than serious projects.
Which tasks to use GPT-4.1-mini for?
- Casual or low-stakes experiments (e.g., testing basic chatbot responses)
- Quick, informal queries that don’t require detailed answers
Where it struggles: In tasks requiring high output quality better contextual understanding.
My take: Stick with the full GPT-4.1 if you want decent help.
GPT-4.5 (Research Preview)
“Use this model for creative writing”
– Andrej Karparthy
GPT-4.5 model puts “art” in “Smart”. The model is suitable for creative writing and ideation. It excels at generating imaginative and enticing content, making it perfect fo tasks like storytelling, poetry, brainstorming, and marketing content. This model is often prone to inconsistencies or factual inaccuracies, its creative strength makes it a valuable tool for content creators looking to go beyond the usual.
Which tasks to use GPT-4.5 for?
- Writing creative stories, poems, or scripts (e.g., drafting a short story or poem)
- Brainstorming advertising slogans or marketing taglines (e.g., catchy campaign ideas)
- Exploring unusual or imaginative concepts (e.g., generating fantasy world ideas)
- Ideation sessions for content creators or artists
Where it struggles: Less consistent factual accuracy and stability; not recommended for mission-critical or technical reasoning tasks.
My take: A promising model for creative professionals who want to experiment with AI-generated ideas and prose.
Deep Research Tool
“Use this for deep research”
– Andrej Karparthy
“Run deep research” tool is an advanced feature that combines the power of ChatGPT models with real-time web searches and multi-source data retrieval. It is designed to provide thorough and up-to-date answers. This tool synthesizes information from multiple documents, making it perfect for in-depth research projects, academic work, and other complex investigations. It is great for deep dives like academic work, market research, or policy analysis.
Which tasks to use Deep Research for?
- Academic research that needs the latest studies and papers (e.g., compiling a literature review)
- Market research that requires up-to-date industry trends (e.g., analyzing competitor strategies)
- Policy and legal analysis involving recent legislation (e.g., summarizing new laws or regulations)
Where it struggles: In tasks relying on internet data quality. The responses can be slower due to search and synthesis overhead.
My take: A powerful augmentation for complex, information-heavy tasks where comprehensive and current answers are required.
ChatGPT Version Comparison
Here is a concise summary of all the models currently available in ChatGPT, their details, limitations, and some use cases.
| Version | Description | Best Use Cases & Examples | Limitations |
|---|---|---|---|
| GPT-4o | Balanced, fast, reliable | Emails, blogs, light coding (e.g., refund email, utils) | Not for deep reasoning |
| o3 | Deep reasoning, slower | Legal/scientific analysis, complex debugging | Slower, expensive |
| o4-mini | Very fast, unreliable | Casual testing, experimental | Low accuracy, hallucinations |
| o4-mini-high | Fast, coding/visual claims | Experimental coding demos | Prone to errors |
| GPT-4.5 (Preview) | Creative, imaginative | Storytelling, ads, brainstorming | Less consistent, factual gaps |
| o1 Pro Mode | Legacy advanced reasoning | Legacy systems only | Slow, outdated |
| GPT-4.1 | Fast coding support | Code generation/debugging (e.g., scrapers, fixes) | Limited complex reasoning |
| GPT-4.1-mini | Lightweight, fast, lower quality | Casual experiments, informal queries | Less reliable |
| Run Deep Research | Web-augmented multi-source tool | Academic research, market intel, policy analysis | Depending on web data, slower |
Conclusion
Makers of ChatGPT have made the GPT 4o the default model in the Chatbot for a reason – its just what you need for any day to day support. For difficult and detailed tasks, bring in o3. Its cheaper too now. For some creative flair use GPT-4.5’s, while coders can get quick help from GPT-4.1. Avoid the mini models for anything serious, and rely on the “Run deep research” tool when you need to dig deep and pull in fresh data. We agree with Andrej Karpathy’s opinion for most of the models! Out of the 9 models that ChatGPT currently offers – it’s just 4 models that are really worth your time.
Use this guide and I hope you can save some time and maximize the quality of outputs that you get using ChatGPT!
Anu Madan is an expert in instructional design, content writing, and B2B marketing, with a talent for transforming complex ideas into impactful narratives. With her focus on Generative AI, she crafts insightful, innovative content that educates, inspires, and drives meaningful engagement.
Good Read!