Gemini 2.5 Deep Think

// Overview

Gemini 2.5 Deep Think is Google's enhanced reasoning mode for Gemini 2.5 Pro, which became generally available on 1 August 2025 inside the Gemini app for Google AI Ultra subscribers. Rather than a separate base model, Deep Think is a way of running Gemini 2.5 Pro that lets it think for much longer and explore many lines of reasoning in parallel before it answers.

Its core idea is 'parallel thinking'. Where a normal model follows one chain of thought, Gemini 2.5 Deep Think generates several candidate solutions at the same time, then revises and combines them over time to reach a stronger final answer. Google built it on a sparse mixture-of-experts transformer, accepts text and image input, and gives it a 1M-token context window with up to roughly 192K tokens of output.

Google positioned Gemini 2.5 Deep Think for the hardest math, science, and competition-coding problems. It posted state-of-the-art results on Humanity's Last Exam and LiveCodeBench v6 at launch, and a related variant reached gold-medal standard at the 2025 International Mathematical Olympiad. It has since been superseded by Gemini 3 Deep Think.

// Benchmarks

1. Humanity's Last Exam (no tools)34.8%
2. LiveCodeBench v687.6%
3. MMMU (multimodal reasoning)84%
4. AIME 202599.2%
5. IMO 2025 benchmark (Bronze)60.7%

Scores on a 0–100 scale (25-point gridlines); higher is better. Each benchmark links to its published source.

// Strengths

• Parallel thinking explores and combines multiple solution paths, which lifts performance on genuinely hard, multi-step problems.
• State-of-the-art reasoning at launch: 34.8% on Humanity's Last Exam without tools, ahead of Grok 4 and OpenAI o3.
• Strong competition-level coding: 87.6% on LiveCodeBench v6.
• Elite math, including 99.2% on AIME 2025 and Bronze-level (60.7%) on the 2025 IMO benchmark.
• Large 1M-token context window for working over long documents and codebases.

// Best for

• Hard mathematics and proofs, including olympiad-style and research-level problems.
• Competition-grade and complex algorithmic coding tasks.
• Graduate- and expert-level science reasoning where a single chain of thought is not enough.
• Multi-step analysis that benefits from weighing several hypotheses before answering.
• Long-context problem solving across large documents thanks to the 1M-token window.

// How to access

// Gemini Deep Think — every version

The full lineage of the Gemini Deep Think line, newest first. Every version has its own page — click any to compare specs, benchmarks and pricing.