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Google has worked hard to position itself as a leader in the generative AI space, developing models that compete against many rivals -- including DeepSeek, Grok and OpenAI.
Since 2023, Gemini has been the primary large language model (LLM) family developed by Google. It's an LLM family that is regularly updated with new models and capabilities. In February 2025,Google Gemini 2.0 was released, followed several months later byGoogle Gemini 2.5 Pro.
At the Google I/O conference on May 20, 2025, the Gemini 2.5 Deep Think model was previewed as an enhanced reasoning mode. On Aug. 1, 2025, Gemini 2.5 Deep Think became generally available as a variant of the Gemini 2.5 series, focused on providing more complex reasoning capabilities.
Gemini 2.5 Deep Think is anLLM developed by Google as part of its Gemini 2.5 model family.
The model is specifically optimized as a reasoning model, meaning it can "think" longer than a regular model to figure out, consider or reason over a prompt, before coming to a conclusion and generating an output.
Gemini 2.5 Deep Think is built on a sparsemixture-of-experts transformer architecture. It has native multimodal support for text, image and audio inputs. The model processes up to 1 million input tokens and can generate up to 192,000 output tokens.
The model's core innovation lies in its parallel-thinking approach. With that approach, the model can explore multiple ideas simultaneously, revising and combining them before answering. The model was developed with advancedreinforcement learning methods to support longer reasoning chains.
The publicly released Gemini 2.5 Deep Think model is closely related to the research version that reached a gold‑medal standard at the 2025 International Mathematical Olympiad (IMO). The consumer release trades some of the more complex, hours‑long reasoning functionality for day‑to‑day responsiveness. Even with the tradeoff, Google claims the model still reaches Bronze‑level performance on the 2025 IMO benchmark based on internal evaluations. It also integrates responsibly with safety improvements and automatically works with tools such as code execution and Google Search.
As a focused reasoning model, Google developed Gemini 2.5 Deep Think to be optimized for problems that benefit from step-by-step resolutions and strategic planning. By explicitly dedicating more inference time and training the model to use longer reasoning paths, it can explore different potential answers. Key advantages of Gemini 2.5 Deep Think include the following:
Gemini 2.5 Pro is a strong general‑purpose model. Gemini 2.5 Deep Think, by contrast, is a Gemini variant focused on extended, parallel reasoning and longer, more detailed outputs. In practice, users select 2.5 Pro in the model picker and toggle"Deep Think" for problems that benefit from more deliberation.
Feature | Gemini 2.5 Pro | Gemini 2.5 Deep Think |
Reasoning approach | Linear thinking with | Multi-agent parallel-thinking system. |
Processing method | Sequential reasoning steps. | Multiple AI agents work simultaneously. |
Response time | Standard (seconds). | Extended "thinking time" (minutes). |
Computational cost | Standard compute | Significantly higher resources required. |
Context window | 1 million tokens input. | 1 million tokens input. |
Output capacity | Up to 65,536 tokens. | Up to 192,000 tokens. |
Response length | Standard responses. | Capable of much longer, |
Safety profile | Standard content safety. | Enhanced safety with |
Pricing | $1.25-$15 per million tokens (API). | $249.99/month |
Availability | Widely available via API. | Limited to Ultra subscribers. |
Gemini 2.5 Deep Think's benchmark performance demonstrates state-of-the-art capabilities across multiple evaluation categories.
Benchmark category | Benchmark | Gemini 2.5 Pro | Gemini 2.5 | OpenAI o3 | Grok 4 |
Reasoning | Humanity's Last Exam | 21.6% | 34.8% | 20.3% | 25.4% |
Mathematics | IMO 2025 | 31.6% (No medal) | 60.7% (Bronze medal) | 16.7% (No medal) | 21.4% (No medal) |
Mathematics | AIME 2025 | 88.0% | 99.2% | 88.9% | 91.7% |
Code generation | LiveCodeBench v6 | 74.2% | 87.6% | 72.0% | 79.0% |
Google is implementing a staged rollout approach for Gemini 2.5 Deep Think. It prioritizes high-value subscribers and developers while gradually expanding access to broader audiences.
Access options include the following:
Sean Michael Kerner is an IT consultant, technology enthusiast and tinkerer. He has pulled Token Ring, configured NetWare and been known to compile his own Linux kernel. He consults with industry and media organizations on technology issues.
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