
Stop wasting time with the wrong ChatGPT model — here's how to choose the right one
OpenAI has released an array of ChatGPT models since the chatbot first launched, each with different names, capabilities, and use cases. What started as a single AI assistant has evolved into a complex lineup that can leave even regular users scratching their heads about which version to choose.
The reality is that different ChatGPT models excel at different tasks. Some are built for speed and everyday conversations, while others are designed for complex reasoning and technical problem-solving.
Choosing the wrong model can mean waiting longer for responses or getting subpar results for your specific needs. This guide breaks down OpenAI's current model lineup, helping you understand what each version does best and how to use it.
GPT-4o is OpenAI's flagship model and the best starting point for most users. It combines the intelligence of the original GPT-4 with significantly faster response times and improved capabilities across text, voice, and vision.
What it's good for: GPT-4o excels at everyday tasks that most people use ChatGPT for. It can brainstorm ideas for your next project, summarize long articles or reports, write and edit emails, proofread documents, and help with creative writing. It's also excellent at analyzing images, translating languages, and handling voice conversations.
When to use it: Choose ChatGPT GPT-4o when you need a reliable, fast model for general-purpose tasks. It's particularly useful when you're working with images, need quick translations, or want to have voice conversations with ChatGPT. If you're unsure which model to use, GPT-4o is usually your best bet.
OpenAI's co-founder Sam Altman describes GPT-4.5 as "the first model that feels like talking to a thoughtful person." It represents a step forward in making AI conversations feel more natural and nuanced.
What it's good for: This model shines in situations requiring emotional intelligence and tactful communication. It can help reframe difficult conversations with colleagues, craft diplomatically worded emails, navigate sensitive topics, and provide thoughtful advice on interpersonal situations.
When to use it: Pick GPT-4.5 when you need help with delicate communication, creative collaboration, or brainstorming sessions where you want more nuanced, human-like responses.
It's particularly valuable for workplace communication, relationship advice, or any situation where tone and empathy matter.
The o3 series represents OpenAI's most advanced reasoning models, with particular strength in technical and scientific tasks.
What they're good for: o3 excels at complex coding projects, advanced mathematics, scientific analysis, strategic planning, and multi-step technical problems. o3-mini handles similar tasks but focuses on speed and cost-efficiency for simpler coding and math problems.
When to use them: Use ChatGPT o3 for your most challenging technical work — complex software development, advanced mathematical modeling, extensive research projects, or strategic business planning.
Choose o3-mini for everyday coding tasks, basic programming questions, quick prototypes, and straightforward technical problems.
The newest addition to OpenAI's lineup, o4 mini is designed for users who need reasoning capabilities but prioritize speed and cost-efficiency.
What it's good for: o4 mini excels at quick technical tasks, fast STEM calculations, visual reasoning with charts and data, extracting information from documents, and providing rapid summaries of scientific or technical content.
When to use it: Choose ChatGPT o4 mini when you need reasoning capabilities but can't wait for the slower, more comprehensive models. It's perfect for quick math problems, rapid data analysis, fast coding help, or when you need multiple quick answers rather than one deep analysis.
For everyday use: Start with GPT-4o. It handles most common tasks efficiently and works with text, images, and voice.
For sensitive communication: Use GPT-4.5 when tone, empathy, and nuanced understanding matter most.
For complex analysis: Choose o1 or o3 when you need thorough, step-by-step reasoning and accuracy is more important than speed.
For quick technical help: Pick o4 mini when you need smart answers fast, especially for math, coding, or data analysis.
Get instant access to breaking news, the hottest reviews, great deals and helpful tips.
Now that you've learned how to pick the right ChatGPT model for any task, why not take a look at some of our other useful ChatGPT guides?
Check out I've been using ChatGPT since its release — here's 5 tips I wish I knew sooner and ChatGPT has added a new image library — here's how to use it.
And, if you want to keep your data private by opting out of training, we've got you covered.

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles


Forbes
an hour ago
- Forbes
Artificial Intelligence Collaboration and Indirect Regulatory Lag
WASHINGTON, DC - MAY 16: Samuel Altman, CEO of OpenAI, testifies before the Senate Judiciary ... More Subcommittee on Privacy, Technology, and the Law May 16, 2023 in Washington, DC. The committee held an oversight hearing to examine A.I., focusing on rules for artificial intelligence. (Photo by) Steve Jobs often downplayed his accomplishments by saying that 'creativity is just connecting things.' Regardless of whether this affects the way you understand his legacy, it is beyond the range of doubt that most innovation comes from interdisciplinary efforts. Everyone agrees that if AI is to exponentially increase collaboration across disciplines, the laws must not lag too far behind technology. The following explores how a less obvious interpretation of this phrase will help us do what Jobs explained was the logic behind his genius The Regulatory Lag What most people mean when they say that legislation and regulation have difficulty keeping pace with the rate of innovation because the innovation and its consequences are not well known until well after the product hits the market. While that is true, it only tells half of the story. Technological innovations also put more attenuated branches of the law under pressure to adjust. These are second-order, more indirect legal effects, where whole sets of laws—originally unrelated to the new technology—have to adapt to enable society to maximize the full potential of the innovation. One classic example comes from the time right after the Internet became mainstream. After digital communication and connectivity became widespread and expedited international communication and commercial relations, nations discovered that barriers to cross-border trade and investment were getting in the way. Barriers such as tariffs and outdated investment FDI partnership requirements—had to be lowered or eliminated if the Internet was to be an effective catalyst to global economic growth. Neoliberal Reforms When the internet emerged in the 1990s, much attention went to laws that directly regulated it—such as data privacy, digital speech, and cybersecurity. But some of the most important legal changes were not about the internet itself. They were about removing indirect legal barriers that stood in the way of its broader economic and social potential. Cross-border trade and investment rules, for instance, had to evolve. Tariffs on goods, restrictions on foreign ownership, and outdated service regulations had little to do with the internet as a technology, but everything to do with whether global e-commerce, remote work, and digital entrepreneurship could flourish. These indirect legal constraints were largely overlooked in early internet governance debates, yet their reform was essential to unleashing the internet's full power. Artificial Intelligence and Indirect Barriers A comparable story is starting to unfold with artificial intelligence. While much of the focus when talking about law and AI has been given to algorithmic accountability and data privacy, there is also an opportunity for a larger societal return from AI in its ability to reduce barriers between disciplines. AI is increasing the viability of interdisciplinary work because it can synthesize, translate, and apply knowledge across domains in ways that make cross-field collaboration more essential. Already we are seeing marriages of law and computer science, medicine and machine learning, environmental modeling, and language processing. AI is a general-purpose technology that rewards those who are capable of marrying insights across disciplines. In that sense, the AI era is also the era of interdisciplinary boundary-blurring opportunities triggered by AI are up against legal barriers to entry across disciplines and professions. In many professions, it requires learning a patchwork of licensure regimes and intractable definitions of domain knowledge to gain the right to practice or contribute constructively. While some of these regulations are generally intended to protect public interests, they can also hinder innovation and prevent new interdisciplinary practices from gaining traction. To achieve the full potential of AI-enabled collaboration, many of these legal barriers need to be eliminated—or at least reimagined. We are starting to see some positive movements. For example, a few states are starting to grant nurse practitioners and physician assistants greater autonomy in clinical decision-making, and that's a step toward cross-disciplinary collaboration of healthcare and AI diagnostics. For now, this is a move in the right direction. However, In some other fields, the professional rules of engagement support silos. This must change if we're going to be serious about enabling AI to help us crack complex, interdependent problems. Legislators and regulators cannot focus exclusively on the bark that protects the tree of change, they must also focus on the hidden network of roots that that quietly nourish and sustain it.

Engadget
an hour ago
- Engadget
Foreign propagandists continue using ChatGPT in influence campaigns
Chinese propaganda and social engineering operations have been using ChatGPT to create posts, comments and drive engagement at home and abroad. OpenAI said it has recently disrupted four Chinese covert influence operations that were using its tool to generate social media posts and replies on platforms including TikTok, Facebook, Reddit and X. The comments generated revolved around several topics from US politics to a Taiwanese video game where players fight the Chinese Communist Party. ChatGPT was used to create social media posts that both supported and decried different hot button issues to stir up misleading political discourse. Ben Nimmo, principal investigator at OpenAI told NPR , "what we're seeing from China is a growing range of covert operations using a growing range of tactics." While OpenAI claimed it also disrupted a handful of operations it believes originated in Russia, Iran and North Korea, Nimmo elaborated on the Chinese operations saying they "targeted many different countries and topics [...] some of them combined elements of influence operations, social engineering, surveillance." This is far from the first time this has occurred. In 2023, researchers from cybersecurity firm Mandiant found that AI-generated content has been used in politically motivated online influence campaigns in numerous instances since 2019. In 2024, OpenAI published a blog post outlining its efforts to disrupt five state-affiliated operations across China, Iran and North Korea that were using OpenAI models for malicious intent. These applications included debugging code, generating scripts and creating content for use in phishing campaigns. That same year, OpenAI said it disrupted an Iranian operation that was using ChatGPT to create longform political articles about US elections that were then posted on fake news sites posing as both conservative and progressive outlets. The operation was also creating comments to post on X and Instagram through fake accounts, again espousing opposing points of view. "We didn't generally see these operations getting more engagement because of their use of AI," Nimmo told NPR . "For these operations, better tools don't necessarily mean better outcomes." This offers little comfort. As generative AI gets cheaper and smarter , it stands to reason that its ability to generate content en masse will make influence campaigns like these easier and more affordable to build, even if their efficacy remains unchanged.

Business Insider
an hour ago
- Business Insider
The Googlers behind NotebookLM are launching their own AI audio startup. Here's a sneak peek.
Some of the key people behind Google's viral AI podcasting app NotebookLM have launched a new startup, and it just unveiled its first product. NotebookLM went viral last year for letting users create AI-generated podcasts about any topic they liked. Some even called it Google's ChatGPT moment. NotebookLM team lead Raiza Martin, designer Jason Spielman, and engineer Stephen Hughes learned from building the app that a surprising number of people actually learn best through audio—not necessarily through text like ChatGPT. They also learned that building a product outside a tech giant like Google is much faster. So, in December 2024, they left Google to launch their own startup, Huxe, which has been operating in stealth mode ever since. On Thursday, it launched a consumer AI app that connects to users' email, calendar, and other personal feeds and generates a daily audio briefing tailored just for them. "People just really seem to digest information more clearly when it's in that audio form," Spielman told Business Insider. Huxe declined to disclose its investors and what it's raised so far. San Francisco venture firm Conviction is one investor, according to an X post from its partner Pranav Reddy. Huxe creates personalized audio Huxe aims to create a personalized feed of AI audio content so users spend less time locked onto their screens and focus more on experiencing the world around them, Martin told Business Insider. Here's what a daily audio briefing from Huxe could go like, Martin says: Good morning! Here are your latest emails. This person has followed up five times — here's what they want. Also, here's what's going on with your meetings today and some headlines you'll care about. Huxe also has a feature called Instant Deep Dive, where users can ask any question, like "What just happened with Nvidia earnings?" or "Summarize OpenAI's latest releases," and get an informative audio response. Users can also interrupt Huxe or ask it questions in real time. Huxe publicly launched the product Thursday, though it is initially only available to a select group of users. It's still early and the product could change, Huxe's cofounders said. Building outside Google was much faster Martin said she was shocked at how quickly they were able to build the first version of Huxe. It only took about a month, she says, mostly because she could just make a decision without needing any approvals from other people. "I think it was just very different building outside of Google," Martin said. "It was great, especially for testing a concept." Spielman has been clear that the idea of Google being slow is a "misconception," he said in a podcast with Sequoia Capital. Still, Google's bureaucracy has gained some infamy in Silicon Valley, and a former Googler has even created a presentation comparing this bureaucracy to " slime mold." Building out of fear isn't the answer Huxe began as an app that lets businesses chat with their data by connecting to tools like Salesforce. While Huxe has since pivoted to focus on consumers, the founders kept a key idea from the original version of Huxe: integrating with your existing apps so the AI can talk across your tools. Still, Huxe faces the risk that a tech giant ends up launching something quite similar and stealing its thunder. Google said at I/O last month that it wants Gemini to be a super-helpful assistant that connects to Gmail and other apps. OpenAI also lets business users connect with Google Drive and use a "record mode" to take notes on meetings. NotebookLM hasn't left the scene, either, and still generates podcasts on specific topics. Google announced Tuesday that it now supports sharing NotebookLM notes publicly. In the end, Martin said you can't build while looking over your shoulder, especially when AI changes so rapidly. "It's hard to be creative and focused when you're in a state of fear," she said. "The newest products that are going to be our everyday products in the future are still to be discovered."