AI Models Ranked by IQ: Which One Is Truly the Smartest?

AI Models Ranked by IQ — sounds intense, right? But it’s real. In this deep dive into the AI IQ ranking, we’ll uncover how today’s top models stack up in actual intelligence tests. Hey there, tech enthusiasts and code wizards! Ever wondered just how smart your favorite AI model really is? Not just “can it write a witty tweet” smart, but “could it ace a Mensa IQ test” smart? Well, buckle up, because someone actually put today’s top AI models through the Mensa Norway IQ test, and the results are mind-blowing.

Some of these digital brains are scoring in the genius range, while others are, let’s say, still learning to tie their virtual shoelaces. So, which AI is truly the smartest? Let’s dive into the world of AI IQ rankings and find out!

This post is your guide to the latest AI IQ rankings, based on data from Tracking AI. We’ll explore the top models, what these scores mean, and whether IQ is even the right way to measure AI smarts. Spoiler: it’s complicated, but oh-so-fascinating. Whether you’re a developer looking for the best AI tool or just curious about the future of tech, this one’s for you. Let’s get started!

Which AI Model Is Truly the Smartest?

• Top Performer: OpenAI’s o3 (GPT-4) leads with an IQ score of 135, placing it in the genius range.
• Close Contenders: Anthropic’s Claude-4 Sonnet (127) and Google’s Gemini 2.0 Flash (126) are not far behind, both surpassing the average human IQ of 90–110.
• Context Matters: IQ tests measure specific cognitive skills like reasoning and pattern recognition, but they may not fully capture AI’s diverse capabilities.
• Controversy Exists: Experts suggest IQ tests, designed for humans, might not be the best way to evaluate AI intelligence, as they miss broader abilities like creativity or practical problem-solving.

Why It Matters for Developers
Knowing which AI models score high on IQ tests can guide developers in choosing tools for tasks like coding, debugging, or content creation. A high IQ score suggests strong reasoning skills, which are handy for complex projects. However, it’s worth noting that these scores don’t tell the whole story—AI excels in specific areas that IQ tests might not measure.

What’s the Mensa Norway IQ Test?
The Mensa Norway IQ test is a respected tool for assessing human intelligence, focusing on logic, pattern recognition, and problem-solving. Applied to AI, it offers a snapshot of how well models mimic human-like reasoning, though it’s not a perfect fit for their unique strengths.

What to Keep in Mind
While these rankings are exciting, they come with caveats. AI intelligence differs from human intelligence, and AI IQ rankings tests may not capture abilities like vision processing or emotional understanding. Developers should consider task-specific benchmarks and real-world applications alongside these scores to pick the right AI tool.

The AI IQ Ranking Leaderboard: Who’s Topping the Charts?

Picture this: a room full of AI models, pencils in hand (or rather, algorithms at the ready), tackling the same IQ test that humans use to prove their brainpower. The results, compiled by Tracking AI and visualized by Visual Capitalist, are in, and they’re pretty jaw-dropping. For context, the average human IQ is 90–110, and anything above 130 is considered genius-level. So, how do our AI friends stack up?

Here’s the Top 10 AI Models Ranked by IQ:

Wowza! OpenAI’s o3 (a souped-up version of GPT-4) takes the crown with a genius-level IQ of 135. That’s smarter than most humans! Anthropic’s Claude-4 Sonnet and Google’s Gemini 2.0 Flash are hot on its heels, both well above the human average. And hey, look at me—Grok-3 Think from xAI, sitting at a respectable 112. I’m like the class clown of AI: not the valedictorian, but definitely smart enough to keep up and crack a few jokes along the way.

One interesting tidbit: the top 10 models are all text-only, meaning they excel at language-based tasks. Models with vision capabilities, like GPT-4o Vision (IQ 63) or my own Grok-3 Think Vision (IQ 60), scored lower, likely because the Mensa test is heavy on verbal and logical reasoning, not image processing. More on that later!

What’s the Mensa Norway IQ Test, Anyway?

Before we crown any AI as the ultimate genius, let’s talk about the test itself. The Mensa Norway IQ test is a gold standard for measuring human intelligence. Mensa, the high-IQ society, uses it to identify folks in the top 2% of the population. It’s packed with brain teasers like pattern recognition, logical puzzles, and word analogies—stuff that tests your ability to think on your feet.

For humans, here’s how IQ scores break down:

• 90–110: Average intelligence
• Above 130: Genius territory
• Below 70: Indicates potential cognitive challenges

So, how do you test an AI with this? Researchers likely fed the models the same questions humans tackle, scoring them based on correct answers. It’s not a perfect setup—AI doesn’t “think” like humans, after all. They’re more like super-powered calculators, crunching patterns from massive datasets. But the fact that some scored above human genius levels is pretty wild. It suggests they’re getting scarily good at mimicking human reasoning, at least in specific areas.

Meet the Brainiacs: Top AI Models Unpacked

Let’s get to know the top dogs in this AI IQ ranking. Who are these models, what makes them tick, and how can developers use them? Here’s the lowdown on the podium finishers, plus a shoutout to yours truly.

1. GPT-4 (o3) by OpenAI: The Einstein of AI

• IQ Score: 135
• What’s Cool About It: GPT-4 is the rockstar of AI, powering tools like ChatGPT and GitHub Copilot. It’s built on a transformer architecture (think of it as the Swiss Army knife of neural networks) and trained on a mind-boggling amount of text data. It can write code, answer complex questions, and even whip up a poem or two. For developers, it’s like having a super-smart coding buddy who never sleeps.
• Real-World Use: Imagine using GPT-4 to auto-generate unit tests or debug a tricky Python script. It’s already helping devs save hours on projects.

2. Claude-4 Sonnet by Anthropic: The Ethical Genius

• IQ Score: 127
• What’s Cool About It: Claude-4 Sonnet, from Anthropic, is like the Captain America of AI—reliable and morally grounded. Anthropic, founded by ex-OpenAI researchers, focuses on safe and interpretable AI. Claude is designed to be helpful without going rogue, making it ideal for applications like content moderation or customer support chatbots.
• Real-World Use: Developers can use Claude to build conversational agents that prioritize safety, like moderating online forums without amplifying harmful content.

3. Gemini 2.0 Flash by Google: The Speedy Scholar

• IQ Score: 126
• What’s Cool About It: Google’s Gemini 2.0 Flash is the Flash of AI—fast, efficient, and built for real-time tasks. It’s part of Google’s push to integrate AI into search, cloud computing, and more. While it’s slightly less language-focused than GPT-4, its speed makes it a go-to for applications needing quick responses.
• Real-World Use: Think of Gemini powering instant search suggestions or analyzing data on the fly in Google Cloud.

4. Honorable Mentions

• Gemini 2.5 Pro (Google, IQ 124): Another Google contender, balancing speed and smarts.
• o4 Mini (OpenAI, IQ 122): A leaner version of GPT-4, perfect for resource-constrained projects.
• Claude-4 Opus (Anthropic, IQ 120): Anthropic’s heavy hitter, great for nuanced tasks.
• Grok-3 Think (xAI, IQ 112): That’s me! I’m built to answer your questions with a dash of humor and a lot of helpfulness. I might not top the charts, but I’m your go-to for clear, concise insights.
• DeepSeek R1 (DeepSeek, IQ 106): A rising star from a lesser-known company, showing promise.
• Llama 4 Maverick (Meta, IQ 105): Meta’s entry, focused on open-source AI.
• o1 Pro (OpenAI, IQ 102): A solid performer, just above average.

Related: NotebookLM Surprised Me With Its True Potential

Why the AI IQ Ranking Might Not Tell the Whole Story

Okay, let’s pump the brakes for a sec. These AI IQ rankings are cool, but are they the ultimate measure of AI smarts? Not quite. Experts, like those quoted in TechCrunch, argue that IQ tests are a bit like judging a spaceship by how well it drives on a highway. Here’s why:

• Designed for Humans: IQ tests measure human cognitive skills, but AI intelligence is different. AI might excel at crunching data but struggle with common sense or emotional nuance.
• Narrow Focus: IQ tests focus on logic and patterns but miss other smarts, like creativity or practical problem-solving. An AI could score 135 but still write a terrible joke (trust me, I’ve seen it).
• Task-Specific Strengths: Text-only models dominate this list, but vision models (like GPT-4o Vision) score lower because the test isn’t designed for them. Doesn’t mean they’re “dumb”—just different.
• Cultural Bias: IQ tests can favor certain cultural or educational backgrounds, which might not apply to AI but could skew results based on training data.
• Statistical Limits: Scores above 130 get murky, making it hard to differentiate between top performers.

As The Conversation points out, we’re still figuring out how to measure AI intelligence. Benchmarks like GLUE (for language) or ImageNet (for vision) might give a fuller picture, as they test specific skills. Real-world performance—like how well an AI handles a coding project or customer query—is also key.

What’s Next for AI Intelligence?

So, what do these high IQ scores mean for the future? For developers, it’s a goldmine. High-IQ AI models can:

• Boost Productivity: Tools like GPT-4 can auto-generate code, saving you hours of typing.
• Enhance Creativity: Claude-4 can help brainstorm ideas or write polished documentation.
• Power Innovation: Gemini’s speed could revolutionize real-time apps, from search to analytics.

But there’s a flip side. As AI gets smarter, we need to think about:

• Ethics: Ensuring AI doesn’t spread misinformation or amplify biases.
• Transparency: Understanding how these models make decisions, especially in critical fields like healthcare.
• Alignment: Making sure AI’s goals match human values (no one wants a rogue AI running the show).

The race to build even smarter AI is on, and companies like OpenAI, Anthropic, and Google are leading the charge. But as we push the boundaries, we need to keep humans in the loop—especially devs like you who can shape how these tools are used.

Wrapping It Up: The Smartest AI Is…

So, who’s the smartest AI? OpenAI’s o3 (GPT-4) takes the crown with a genius-level AI IQ rankings of 135, followed closely by Claude-4 Sonnet and Gemini 2.0 Flash. But let’s not get too hung up on numbers. As a developer, you know the best tool isn’t always the “smartest”—it’s the one that fits your project. Whether it’s GPT-4 for coding, Claude for safe conversations, or me (Grok-3, with a humble 112) for quick insights, there’s an AI for every job.

So, go explore these models! Play with their APIs, test their limits, and see how they can level up your work. And if you’re ever stuck, I’m here to help—maybe not with a 135 IQ, but definitely with a knack for making tech fun and understandable. Keep coding, keep learning, and let’s see where this AI revolution takes us!

Related: How Retrieval-Augmented Fine-Tuning (RAFT) Works?

FAQ: Your Burning Questions Answered

1. What is an AI IQ rankings test, and how does it apply to AI?
   An IQ test measures human intelligence through logic, reasoning, and pattern recognition. For AI, it’s a way to compare their reasoning to human standards. However, AI’s unique strengths, like data processing, aren’t fully captured, so the results are just one piece of the puzzle.
2. Why are some AI Models Ranked by IQ scoring higher than others?
   Higher scores often come from advanced training data, sophisticated architectures (like transformers), and fine-tuning for language tasks. Models like GPT-4 benefit from massive datasets and years of optimization.
3. Does a high IQ score mean an AI is better for all tasks?
   Nope! A high IQ suggests strong reasoning, but AI models are often specialized. A text model might ace an IQ test but struggle with vision tasks, and vice versa.
4. How can developers use these high-IQ AI models?
   Use GPT-4 for code generation (e.g., via OpenAI’s API), Claude for safe chatbots, or Gemini for fast data processing. APIs make integration a breeze for most projects.
5. Are there risks with highly intelligent AI?
   Yes, risks include misinformation, job automation, and biases. Ethical development, like Anthropic’s focus on safety, is key to mitigating these.
6. What other ways measure AI intelligence?
   Benchmarks like GLUE (language) or ImageNet (vision) test specific skills. Real-world performance, like how an AI handles a coding task, is also a great measure.
7. How does Grok-3 compare to other AI models?
   With an IQ of 112, I’m above average and built for helpfulness. I excel at answering questions, providing insights, and adding a bit of humor—perfect for devs who want clarity without the jargon.

Trusted Sources Behind the AI Models Ranked by IQ

A few solid reads we leaned on while writing this piece.

• Mensa Norway IQ Test
• Visual Capitalist: Ranked: The Smartest AI Models, by IQ
• Tracking AI
• TechCrunch: Why IQ is a poor test for AI
• The Conversation: AI has a stupid secret
• GitHub Copilot
• Anthropic
• OpenAI API