Gemini Deep Think Costs $250 for 5 Prompts

Google’s newest AI model can solve International Mathematical Olympiad problems at a gold medal level, but you’ll need deep pockets to access its advanced reasoning capabilities.

The tech giant officially launched Gemini 2.5 Deep Think on August 1, 2025, exclusively for Google AI Ultra subscribers, who pay $249.99 per month. This positions the model as a premium offering for developers, researchers, and businesses that require sophisticated mathematical and coding capabilities.

What sets Deep Think apart? Unlike traditional AI, which processes queries step by step, this model utilizes parallel thinking techniques to generate multiple solution hypotheses simultaneously, then integrates and refines these approaches before producing final answers. It’s like having several brilliant minds work on your problem simultaneously, then combining their best ideas.

Mathematical Excellence Meets Practical Constraints

The model’s crown jewel achievement came in July, when an advanced version of Gemini Deep Think achieved gold medal status at the 2025 International Mathematical Olympiad, scoring 35 out of 42 points by solving five out of six problems. This marks the first time any AI has officially earned gold at the prestigious competition.

IMO President Gregor Dolinar called Deep Think’s solutions “astonishing” and “clear, precise and most of them easy to follow”. The achievement represents a significant leap from previous AI attempts, which required specialized systems and formal language translation.

Unlike 2024’s silver medal performance, which utilized specialized AlphaProof and AlphaGeometry systems requiring formal language translation, Deep Think operates end-to-end in natural language. This means it can understand problems written in plain English and provide solutions in the same way.

Performance Benchmarks Show Clear Leadership

Beyond mathematical competitions, Deep Think demonstrates impressive capabilities across various benchmarks. The model achieved 87.6% performance on LiveCodeBench coding benchmarks, significantly outperforming OpenAI’s o3 model at 72%. On Humanity’s Last Exam, Deep Think scored 34.8% compared to xAI’s Grok 4 at 25.4%.

These aren’t just abstract numbers. They translate to real-world capabilities in solving complex programming challenges, mathematical proofs, and technical reasoning tasks that stump most humans. The model can process up to 1 million token contexts with 192K token outputs, allowing it to handle extensive documents and generate detailed responses.

The Price of Premium Intelligence

At $250 monthly, Google’s pricing strategy targets professional users rather than casual consumers. To sweeten the deal, first-time subscribers receive 50% off for three months, reducing the initial barriers to premium adoption. This brings the introductory cost to $125 per month before jumping to the full price.

But there’s a catch that frustrates early adopters. Google AI Ultra subscribers receive five Deep Think prompts per day, with limits resetting on a 24-hour rolling basis. Some users calculate this works out to roughly $50 per prompt at the monthly rate. Once you hit the limit, you’re switched back to standard Gemini models.

These restrictions suggest that the computational demands of parallel reasoning come at a significant cost. Running multiple solution paths simultaneously requires substantial processing power, which Google must balance against the need for sustainable service delivery.

Enterprise Strategy Takes Shape

Google isn’t just targeting individual power users. The company plans to release Deep Think, both with and without tool access, to trusted testers via the Gemini API within weeks of the consumer launch. This staged rollout allows enterprise customers to integrate the technology while Google gathers feedback.

The company has also introduced Google AI Ultra for Business as a Workspace add-on, providing enterprise-grade data protection. Business subscribers receive 12,500 monthly credits for additional AI applications, in addition to Deep Think access, making it more attractive for organizations already invested in Google’s ecosystem.

Academic partnerships form another key pillar of Google’s strategy. The company is providing the full IMO gold-medal version to select mathematicians and researchers, fostering collaboration that could yield new mathematical discoveries while refining the system.

Safety Concerns Emerge Alongside Capabilities

With great reasoning power comes great responsibility. Google conducted extensive safety evaluations through its Frontier Safety Framework, examining Critical Capability Levels across autonomy, biosecurity, cybersecurity, and AI research domains.

The evaluations revealed concerning patterns. While Deep Think showed improved content safety compared to standard models, it also demonstrated higher refusal rates for benign requests. More worryingly, the model exhibited increased capabilities in biological and chemical knowledge domains.

Independent researchers have raised alarms about AI systems potentially lowering barriers to biological weapons development. Contemporary foundation models may provide guidance on pathogen synthesis and weaponization techniques; however, Google maintains that Deep Think has not yet reached critical capability thresholds that require additional safeguards.

Competitive Landscape Heats Up

Deep Think’s launch intensifies the AI reasoning race. Both Google and OpenAI achieved IMO gold medal performance in July 2025, but their approaches differed significantly. OpenAI kept its achievement internal, while Google pursued official certification from the IMO committee.

The $250 pricing position puts Google above OpenAI’s ChatGPT Pro at $200 per month, but with potentially superior mathematical capabilities. Google’s integration with existing Workspace and Cloud services adds value beyond pure AI functionality.

Looking ahead, Google’s multi-model strategy spans various capability levels. Users can choose between Gemini 2.5 Flash for quick tasks, Pro for general use, and Deep Think for complex reasoning challenges. This tiered approach enables organizations to optimize costs while leveraging the appropriate level of AI power.

What This Means for Users

For researchers tackling complex mathematical proofs, Deep Think offers unprecedented assistance. Software developers can leverage their coding capabilities to solve intricate programming challenges. Scientists might use it to verify hypotheses or explore solution spaces.

But casual users hoping to explore advanced AI reasoning will find the price steep and usage limits restrictive. The five-prompt daily limit means careful consideration before each query. Is your problem worth $50 of AI reasoning?

CEO Sundar Pichai positioned Deep Think as a tool for “fun Friday night” problem-solving, suggesting Google sees it as a premium experience for technical enthusiasts. Whether enough users will pay premium prices for limited access remains an open question.

The technology works. Deep Think’s mathematical achievements prove AI can match human experts in specialized domains. But transforming that capability into a sustainable business model while managing safety concerns presents ongoing challenges.

Google’s bet on premium AI pricing reflects broader industry trends toward specialized, high-capability models. As computational costs remain high and safety concerns persist, we’re likely to see the emergence of a two-tier AI market: affordable, general-purpose models for everyone, and expensive, specialized systems for those who genuinely need them.

Key Takeaways:

• Google’s Gemini 2.5 Deep Think costs $249.99 monthly, with only five prompts per day.
• The model achieved official gold medal status at the International Mathematical Olympiad.
• Performance benchmarks show significant advantages over competing models in coding and reasoning.
• Enterprise API access and academic partnerships expand beyond consumer offerings.
• Safety evaluations reveal enhanced capabilities in sensitive domains, such as biosecurity.
• Premium pricing strategy targets professional users rather than mass market adoption.