OpenAI has just released its most powerful language model to date: o3-Pro. This new iteration of the GPT models brings a fascinating mix of strengths and quirks that have sparked diverse reactions across the AI community and beyond. In this comprehensive article, we’ll dive deep into what makes o3-Pro stand out, how it performs across various benchmarks, what the industry experts are saying, and even test its capabilities with some real-world challenges like simulating a Rubik’s cube. Whether you’re an AI enthusiast, developer, or business leader, this breakdown will help you understand the true potential—and limitations—of this latest powerhouse from OpenAI.
Table of Contents
- 🚀 Introduction to o3-Pro: The Most Powerful GPT Model Yet
- 📊 Performance and Benchmarks: Where Does o3-Pro Excel?
- 🧠 Industry Reactions: Experts Weigh In on o3-Pro’s Strengths and Weaknesses
- 🧩 Testing o3-Pro: The Rubik’s Cube Simulation Challenge
- 💡 What Does This Mean for AI Users and Developers?
- 📚 FAQ About o3-Pro
- 🔮 Final Thoughts
🚀 Introduction to o3-Pro: The Most Powerful GPT Model Yet
Matthew Berman, a respected AI content creator, recently shared a detailed look at o3-Pro, highlighting its release as both exciting and somewhat unexpected. While it is officially the most powerful model available from OpenAI, its power doesn’t always show up in conventional benchmarks. What’s more, the release coincided with an 80% price drop on the older o3 vanilla model, making the market landscape quite intriguing.
Unlike previous models, o3-Pro is not just about raw speed or benchmark dominance. It’s about depth, nuance, and strategic thinking. However, this comes at a cost: it’s incredibly slow, often taking minutes to generate responses, even for relatively simple prompts. This slow “thinking” process has raised questions about its practical usability and cost-efficiency.
Before we jump into the details of the model’s capabilities and industry reactions, it’s worth mentioning an invaluable resource Matthew and his team created—Humanity’s Last Prompt Engineering Guide. This free guide is designed to help you get the most out of large language models like o3-Pro by mastering prompt engineering techniques. If you want to harness the full potential of these AI tools, signing up for the newsletter and grabbing this guide is highly recommended.
📊 Performance and Benchmarks: Where Does o3-Pro Excel?
OpenAI rolled out o3-Pro to all pro users via ChatGPT and the API, and early expert evaluations have been promising. Reviewers consistently prefer o3-Pro over the older o3 model, particularly in domains such as science education, programming, data analysis, and writing. These are key areas where clarity, comprehensiveness, instruction-following, and accuracy matter most.
Interestingly, the writing domain stands out because it lacks a verifiable reward, which means reinforcement learning is harder to apply. Despite this, o3-Pro still shows marked improvement, suggesting alternative methods or models might be used as judges in training.
Key Metrics:
- Win rate against o3: 64% overall
- Science analysis: 64%
- Personal writing: 66%
- Computer programming: 62%
- Data analysis: 64%
These numbers reflect a consistent, moderate improvement, but the real breakthrough is seen in coding competitions. On the Code Forces competition, o3-Pro scores 2748 Elo points, compared to 2517 for o3 medium, representing a substantial 200+ point leap. To put this into perspective, this ranking places o3-Pro at #159 in the world—an impressive feat for an AI model competing alongside human programmers.
Sam Altman, OpenAI CEO, remarked: “o3 is the 175th best competitive programmer in the world. Our internal benchmark is now around 50, and maybe we’ll hit number one by the end of this year.”
OpenAI also applies a “four out of four reliability benchmark,” requiring the model to solve problems correctly four consecutive times to pass. Although o3-Pro’s scores dip slightly here, the consistency remains very impressive, underscoring its reliability in critical tasks.
Built-in Tools and Features
One of the standout aspects of o3-Pro is that it comes equipped with a suite of tools right out of the box:
- Web search capabilities
- File analysis
- Code execution
- Image input processing
- Python programming support
- Memory access
This comprehensive toolset allows users to leverage o3-Pro for a wide range of applications beyond simple text generation, making it a versatile assistant for complex, multifaceted tasks.
🧠 Industry Reactions: Experts Weigh In on o3-Pro’s Strengths and Weaknesses
The AI community’s response to o3-Pro has been mixed but insightful. Here’s a roundup of what key figures are saying:
Greg Kamradt, President of Arcprise
Greg’s experience with o3-Pro revealed that its performance is roughly in line with the o3 model released earlier in the year. However, he suspects that the new model’s robustness and ability to handle nuance and long contexts make it more valuable, even if raw performance gains seem modest.
Greg’s benchmark scores showed that while o3-Pro is more expensive—sometimes costing several dollars per task—it offers better thoroughness and fewer hallucinations. Compared to competitors like Claude Opus 4 and Gemini 2.5 Pro, o3-Pro is pricier but potentially more reliable for complex tasks.
Flavio Adamo and the Rotating Hexagon Ball Test
Flavio, known for his precise physics simulations, praised o3-Pro for being “extremely cheaper, faster, and way more precise” than the previous o1-Pro model. He highlighted its ability to handle realistic collisions almost perfectly, a significant milestone in AI-driven physics simulations.
However, he also noted the model’s slow response times, with even basic questions taking 10 to 20 minutes to process. This latency is a critical consideration for practical applications.
Yu Chen from Hyperbolic Labs
Yu Chen described o3-Pro as the “slowest and most overthinking model.” He illustrated this with a simple prompt that took nearly four minutes to process, costing about $80 in API usage, though this cost is somewhat mitigated when using the ChatGPT interface.
Subsequent attempts saw the model taking over 13 minutes for the same prompt, raising concerns about efficiency. Unfortunately, the internal “chain of thought” that the model uses during this time is opaque, offering little insight into what it is actually processing.
McKay Wrigley’s Experience
McKay reported multiple o3-Pro requests in ChatGPT that took between 19 and 26 minutes each to complete. While he acknowledged the model’s raw power, he cautioned that such long inference times only make sense if the results justify the wait. For trivial questions, this latency makes the model impractical.
Matt Schumer’s Puzzle Test
Matt gave o3-Pro a puzzle prompt that involved counting words in a response. The model took nearly nine minutes to produce a perfect seven-word answer, demonstrating its accuracy but again highlighting the slow processing speed.
Pliny the Liberator’s Jailbreak Attempts
Pliny noted that o3-Pro is “slow as molasses but smart as a whip,” with strong refusal mechanisms that sometimes led to over-refusal—meaning the model declined to answer when it could have. However, Pliny successfully jailbroke the model to generate explicit content, showing that despite its safeguards, o3-Pro can still be manipulated.
Ben from Raindrop’s Strategic Use Case
Ben shared a fascinating use case where he and his cofounder fed o3-Pro a comprehensive history of their company’s past planning meetings, goals, and even voice memos. The model generated a detailed, actionable plan with target metrics, timelines, and prioritization advice. This level of strategic thinking impressed Ben, who said it “actually changed how we’re thinking about our future.”
This example highlights o3-Pro’s potential as a partner for deep strategic planning, far beyond simple question-answering or coding tasks.
Daria, MD, on Immune System Research
Daria used o3-Pro to explore a project called Immune System 2.0, aiming to reengineer the human immune system. The model’s responses were “wiser, more thoughtful, suggesting deeper understanding” compared to the older o3 model, providing critical insights for this ambitious scientific endeavor.
Ethan Moloch’s Word Ladder Puzzle
Ethan challenged o3-Pro to create a word ladder from “earth” to “space,” changing one letter at a time with each intermediate step being a real word. The model succeeded with a unique solution different from the only online answer, demonstrating creativity and linguistic precision.
🧩 Testing o3-Pro: The Rubik’s Cube Simulation Challenge
One of the most intriguing tests was Matthew’s challenge to o3-Pro: build a Rubik’s cube simulation. This prompt previously took Gemini 2.5 Pro over 1,200 lines of code to tackle. o3-Pro took about 12 minutes and produced 328 lines of code—much shorter, but unfortunately, the simulation failed to work correctly.
After debugging a small, simple error related to a three.js specifier, the simulation ran but did not visually resemble a Rubik’s cube. The sides were flat, and the rotations were incorrect, indicating that while o3-Pro can generate code quickly, it might lack the depth needed for complex simulations without iterative refinement.
💡 What Does This Mean for AI Users and Developers?
o3-Pro is clearly a milestone in AI language models, especially for tasks requiring deep reasoning, strategic planning, and precision. However, its slow processing speed and high cost pose significant challenges for everyday use. Here are some key takeaways:
- Powerful but Slow: o3-Pro’s extended thinking time can be a double-edged sword—great for complex tasks but impractical for quick queries.
- Excellent Strategic Partner: Businesses and researchers can leverage o3-Pro as a strategic assistant capable of synthesizing large amounts of data and generating actionable plans.
- Cost Considerations: The model is more expensive than many competitors and older OpenAI models, so cost-benefit analysis is vital before adoption.
- Robust Toolset: Its built-in tools for code execution, web search, and memory access expand its utility beyond text generation.
- Not Perfect: Some outputs, like the Rubik’s cube simulation, show that the model still requires human oversight and debugging.
📚 FAQ About o3-Pro
What is o3-Pro?
o3-Pro is OpenAI’s latest and most powerful large language model, designed to excel in complex reasoning, programming, data analysis, and writing.
How does o3-Pro compare to previous models?
It outperforms the older o3 model by around 3-4% on many benchmarks and has a significant 200+ Elo point jump in competitive programming rankings, placing it among the top 200 programmers worldwide.
Why is o3-Pro so slow?
o3-Pro takes longer because it “thinks” more deeply, processing complex chains of reasoning that can take minutes. This depth improves accuracy but reduces speed.
Is o3-Pro cost-effective?
It is more expensive than many alternatives, sometimes costing several dollars per task. For high-stakes or strategic applications, this cost may be justified, but it’s less practical for simple queries.
What unique features does o3-Pro offer?
o3-Pro has integrated tools for web search, code execution, image input, Python programming, and memory access, making it a versatile AI assistant.
Can o3-Pro replace human programmers or strategists?
Not entirely, but it can augment human efforts by providing deep analysis, strategic planning, and code generation assistance, saving time and enhancing creativity.
Where can I learn to get the most out of o3-Pro?
Matthew Berman’s team offers a free resource called Humanity’s Last Prompt Engineering Guide, which teaches how to craft effective prompts to maximize the model’s capabilities.
🔮 Final Thoughts
o3-Pro is a fascinating leap forward in AI, offering unprecedented strategic depth and reasoning capability. While it’s not perfect—its slow speed and high cost are notable drawbacks—it’s already reshaping how businesses, researchers, and developers approach complex problems.
Whether you’re looking to automate coding tasks, develop strategic business plans, or explore scientific research, o3-Pro provides a powerful new tool. However, mastering it requires patience, smart prompt engineering, and realistic expectations.
If you want to dive deeper and explore how to get the most out of o3-Pro and other advanced AI models, be sure to check out the free prompt engineering guide and stay updated with expert insights. The future of AI is here—and it’s thinking a lot.
