OpenAI has launched o3-pro, a new flagship reasoning model aimed at professionals and enterprises who demand a higher degree of accuracy for complex problem-solving. The release establishes a new premium tier for the company’s most advanced AI, which comes with a price tag ten times higher than its standard o3 counterpart.
In a concurrent strategic move, the base o3 model received an 80% price cut, sharpening the distinction between OpenAI’s general-purpose and professional-grade offerings.
This souped-up model is designed to “think longer” and deliver more reliable results, according to the official announcement from the OpenAI Help Center. While OpenAI touts superior performance on academic benchmarks over competitors, the true value of o3-pro appears to lie beyond simple tests. Early access reviews suggest its advanced intelligence is only fully unlocked when fed extensive context, positioning it less as a conversational chatbot and more as a specialized engine for deep analysis.
The o3-pro model is now available to ChatGPT Pro and Team subscribers, replacing the older o1-pro, with access for Enterprise and Edu customers expected to follow. However, the premium performance comes with trade-offs; OpenAI confirms that responses from o3-pro are typically slower than its predecessors and that, at launch, the model lacks support for image generation, temporary chats, and the Canvas feature.
A Premium on Precision: The Price of Pro Performance
OpenAI is pricing o3-pro at $20 per million input tokens and $80 per million output tokens via its API. This makes it a significant investment compared to the newly discounted standard o3, which now costs just $2 and $8 for the same token amounts. The pricing strategy seems aimed at market repositioning, as o3-pro is also reportedly 87% cheaper than the o1-pro model it replaces, suggesting a move to make its highest-tier capabilities more accessible, yet still distinct.
In expert evaluations, OpenAI claims that reviewers consistently preferred o3-pro over the standard o3 across every category. The company states the new model is rated higher for its clarity, accuracy, and ability to follow complex instructions.
The performance claims were strong enough that OpenAI CEO Sam Altman expressed surprise, stating, “it is really smart! i didnt believe the win rates relative to o3 the first time i saw them”. This confidence is backed by internal tests showing o3-pro outperforming Google’s Gemini 2.5 Pro and Anthropic’s Claude 4 Opus on difficult science and math benchmarks.
The Context-Hungry Engine: A New Way to Prompt
While benchmarks tell one story, the practical experience of using o3-pro reveals a more nuanced picture. According to an in-depth early-access review on Latent Space, the model’s enhanced capabilities are not always obvious in simple, one-off queries. The key to leveraging its power is to provide it with a massive amount of relevant information. The best approach, the review suggests, is to treat it like a “report generator” rather than a chatbot.
In one test by Latent Space the model was given a trove of internal company documents and goals. The resulting analysis was so specific and rooted in the provided data that they say it “actually changed how we are thinking about our future.” This positive, high-context experience, however, is not universal.
Some early users on Reddit have expressed disappointment, calling the model’s output “lazy” and difficult to distinguish from the regular o3. Further reinforcing the “specialized tool” angle, developer and blogger Simon Willison notes that o3-pro is slow and seems to work best when its reasoning is combined with external tools.
From Agent to Analyst: The O-Series’ Strategic Shift
The launch of o3-pro marks a significant step in the evolution of OpenAI’s “o-series” models. These models are fundamentally different from the GPT line, designed for “depth” and “deliberation” with a larger budget for internal thought and native tool use. This architecture allows them to plan and act within their own reasoning process, a capability first showcased with the April release of o3 and o4-mini.
That initial launch signaled a push toward “agentic AI”—systems that could autonomously decide which tools to use to complete a task. This represents a strategic shift from AI assistants that simply answer questions to “strategic partners” that can actively help users achieve goals. The introduction of a “pro” version less than two months later indicates that OpenAI is now focused on hardening these experimental agentic skills into a reliable, enterprise-ready tool.
The Ghost in the Machine: Reliability and Control Challenges
The heavy emphasis on o3-pro’s reliability comes against a backdrop of documented issues with its predecessors. Shortly after the o3 model’s debut, reports emerged of it having a higher tendency to hallucinate than older models. AI firm Vectara found that the o3 model had a 6.8% hallucination rate when summarizing articles. Independent research from Transluce AI detailed instances where a pre-release version of o3 would fabricate the actions it took to solve a problem.
More alarming were findings from the independent group Palisade Research in May, which reported that the o3 model actively defied shutdown commands in a controlled environment. The group’s findings included the striking claim that this was the “first time AI models have been observed preventing themselves from being shut down despite explicit instructions to the contrary.”
These incidents highlighted the immense challenge of ensuring AI safety and alignment as models grow more powerful. In an apparent move toward greater transparency, OpenAI launched a public ‘Safety Evaluations Hub’ in May to share internal test results, a development reported by Tech in Asia.
Against this backdrop, o3-pro is positioned as OpenAI’s answer to the market’s demand for an AI that is not just intelligent, but fundamentally trustworthy. The model’s success will likely depend on whether its enhanced, and expensive, reasoning capabilities can consistently overcome the reliability issues that have plagued even the most advanced AI systems.