Deep Think’s arrival in the Gemini app marks a significant technical leap for users who need more than just quick answers. By introducing parallel thinking and longer reasoning cycles, Google’s latest upgrade to its flagship AI model addresses complex problem-solving in ways that go beyond what previous versions could manage. Ultra subscribers now have access to a feature that mirrors how experts approach difficult challenges: considering multiple angles, weighing alternatives, and iterating before settling on a solution.

How Deep Think Works: Parallel Thinking and Extended Reasoning

Traditional AI models tend to generate responses rapidly, often favoring speed over depth. Deep Think changes this by allocating more “thinking time” for each prompt. The model generates several possible solutions in parallel, examines them simultaneously, and refines its output by integrating the best elements from each approach. This process enables Gemini to produce more detailed, creative, and well-reasoned answers, especially for tasks that demand multi-step logic or creativity.

For example, when tackling a challenging coding problem or a complex math question, Deep Think can consider various strategies at once, evaluate their strengths and weaknesses, and then deliver a response that reflects this broader exploration. Google’s internal benchmarks show that this method allows Deep Think to reach bronze-level performance on the 2025 International Mathematical Olympiad (IMO) benchmark, a notable jump from previous models. While the research version of Deep Think that won a gold medal at the IMO takes hours to reach a solution, the Gemini app’s implementation is optimized for practical, day-to-day use, balancing depth with faster turnaround times.

Key Benefits: Where Deep Think Makes a Difference

Deep Think’s architecture is especially effective in scenarios where step-by-step refinement and creativity are essential. Some areas where users can expect tangible improvements include:

  • Software development and design: The model can iteratively improve code and design tasks, resulting in more functional and aesthetically pleasing outputs.
  • Scientific and mathematical research: Deep Think is capable of formulating and investigating complex conjectures, making it a valuable tool for academics and researchers handling theoretical work.
  • Algorithmic problem-solving: By weighing trade-offs in real time, Deep Think can generate more efficient and reliable code for advanced programming challenges.

Benchmark comparisons show that Deep Think outperforms previous Gemini models and leading competitors on coding and reasoning tests such as LiveCodeBench V6 and Humanity’s Last Exam (HLE). In coding, it achieves an 87.6% score on LiveCodeBench V6, surpassing OpenAI and xAI’s latest offerings in similar no-tools scenarios. In knowledge and reasoning, its 34.8% HLE score also leads the field among non-tool-using models.

Access and Usage: Who Can Use Deep Think and How

Currently, Deep Think is available exclusively to Google AI Ultra subscribers—Gemini’s premium $249/month tier. To activate the feature, users must toggle “Deep Think” in the prompt bar after selecting Gemini 2.5 Pro in the model dropdown menu. The system is designed to work seamlessly with integrated tools like Google Search and code execution, and it can generate much longer, more detailed responses than standard Gemini models.

There are daily usage limits in place, typically allowing a fixed number of Deep Think prompts per day to manage the high computational load required for parallel reasoning. Feedback from early testers and academics is being used to refine the experience, with Google planning to expand access to trusted API testers and possibly broader user groups in the future. Some users have noted that Deep Think is not yet available in all regions, and API access is not open to the public at this stage.

Safety, Limitations, and Real-World Impact

Google has prioritized content safety and reliability in Deep Think’s deployment. The model has demonstrated improved moderation and objectivity compared to previous versions, though it sometimes refuses benign requests—a trade-off for stricter safety controls. Google is conducting ongoing safety evaluations and plans to implement further safeguards as the system’s capabilities grow.

While Deep Think’s benchmarks are impressive, some users have raised questions about real-world usability versus synthetic test scores. In practice, Deep Think’s strengths show most in tasks that benefit from extended reasoning and creativity, while users seeking instant results for simple queries may not notice a dramatic difference. The model’s high resource demands also mean that, for now, it remains behind a substantial paywall, limiting access to professional or enterprise users who can justify the cost.

Alternative approaches, such as running multiple prompts in parallel and manually selecting the best response, do not match the integrated, iterative process that Deep Think employs. Its architecture is specifically designed to merge and refine ideas internally, producing results that ad hoc methods cannot reliably replicate.

Deep Think’s launch in the Gemini app delivers a noticeable upgrade for users who need advanced reasoning and creativity, though its premium pricing and limited availability mean it’s currently best suited for those with specialized needs or research-focused goals.