A “slow-thinking” mode built for high-difficulty logic problems
If ChatGPT 5.1 is a fast, versatile all-round assistant, ChatGPT 5.1 Thinking is a more deliberate expert advisor. It adds a unique “thinking buffer,” running multi-angle reasoning and internal checks before responding. While it may generate a bit slower than the standard version, it delivers a major boost in accuracy and logical rigor for complex mathematical proofs, competitive-level algorithmic coding, and deep scientific analysis.
Clearer logic, more actionable conclusions
For mathematical derivations, logic analysis, or decision plans, it’s better at breaking problems into actionable mini-steps, progressing systematically, and giving rationale and conclusions at key points—helping avoid answers that seem correct but aren’t actually useful.
A powerhouse for STEM—no more vague, “sort-of-right” answers
Built for tasks with extremely low tolerance for error—advanced math, physics modeling, and complex data analysis. It can spot logical traps hidden in the prompt or requirements and proactively validate through multiple passes. For hardcore tasks that require very long reasoning chains, it stays focused and consistent end-to-end, significantly reducing logical gaps.
The key difference is the "thinking mode." The standard version focuses on speed and fluency for most daily tasks, while the Thinking version requires "deep thinking" and "self-reflection" before output. It's a bit less responsive, but for tough problems, its accuracy is much higher than the standard version.
That’s exactly how it’s designed. After you ask a question, it runs multiple rounds of reasoning and internal checks in the background—like a human expert pausing to think before answering a tough problem. Those extra seconds trade for higher-quality answers that stand up to scrutiny.
It’s ideal for “hardcore” scenarios—writing complex algorithmic code, checking logic bugs, deriving mathematical formulas, building rigorous academic arguments, or crafting thorough business strategy analyses. For casual small talk, it may feel overly serious.
It doesn’t just write code—it helps optimize architecture. Share inefficient code, and it can use mathematical reasoning to find bottlenecks, propose refactors with better time complexity, anticipate edge cases, and even write defensive code in advance.
We provide a free quota so you can experience the deep-thinking model. Since it consumes relatively high compute resources, we recommend upgrading to a subscription plan for frequent use. See the pricing page for plan benefits and quotas.
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