Google has unveiled Gemini 2.5 Pro Experimental, its latest AI model, bringing significant improvements in structured reasoning, multimodal capabilities, and long-context comprehension. The model, which is currently available to Gemini Advanced and Google AI Studio users, is expected to roll out to Vertex AI soon.
This release places Gemini 2.5 Pro in direct competition with xAI’s Grok 3 Beta, OpenAI’s O3-Mini High, and DeepSeek’s latest models, all of which have recently introduced enhanced AI reasoning capabilities.
How Gemini 2.5 Pro Improves AI Reasoning
One of the most notable upgrades in Gemini 2.5 Pro is its ability to apply multi-step logical verification before generating responses, improving its accuracy in complex problem-solving.
Google describes this as a refinement of its structured reasoning approach, ensuring better decision-making and reliability in research, enterprise, and AI-powered assistance tools, writing “[Gemini] 2.5 Pro ships today with a 1 million token context window (2 million coming soon), with strong performance that improves over previous generations”
How Does Gemini 2.5 Pro Compare?
Google has positioned Gemini 2.5 Pro as an advanced reasoning model, but its true capabilities come into focus when compared across various performance dimensions against competing AI models, including OpenAI’s O3-Mini High and GPT-4.5, xAI’s Grok 3 Beta, Anthropic’s Claude 3.7 Sonnet, and DeepSeek R1. The results show a model that leads in some areas while facing competition in others.
Reasoning & Knowledge
One of the most critical aspects of modern AI models is their ability to reason through complex problems and general knowledge tasks. On Humanity’s Last Exam, a multimodal test covering mathematics, humanities, and natural sciences, Gemini 2.5 Pro scored 18.8%.
This places it ahead of OpenAI’s O3-Mini High, which achieved 14.0%, and DeepSeek R1, which trailed further behind at 8.6%. While Gemini 2.5 Pro outperforms these competitors, no direct comparison against OpenAI’s more advanced GPT-4.5 was provided, making it difficult to determine how Google’s model stacks up against OpenAI’s top-tier reasoning AI.
Mathematical Performance
Mathematical reasoning has been a focal point for AI development, particularly in solving competition-style problems. Gemini 2.5 Pro achieved a 92.0% accuracy rate on the AIME 2024 dataset, a benchmark designed to assess a model’s ability to solve advanced algebra and number theory problems.
This score is significantly higher than OpenAI’s GPT-4.5, which managed only 36.7%, and DeepSeek R1, which landed at 79.8%. However, when looking at models capable of multiple-attempt responses, Grok 3 Beta and DeepSeek R1 performed slightly better, both scoring 93.3%. This suggests that while Gemini 2.5 Pro is highly capable in a single-attempt setting, other models may have slight advantages when allowed to iterate on their answers.
Coding & Agentic AI
Code generation and autonomous AI-assisted software development remain among the most competitive benchmarks. On LiveCodeBench, a widely used standard for evaluating AI-assisted coding capabilities, OpenAI’s O3-Mini High leads with a 74.1% accuracy rate, surpassing Gemini 2.5 Pro’s 70.4%.
Despite this, Gemini 2.5 Pro takes the lead in code editing tasks, particularly on the Aider Polyglot benchmark, where it scores 74.0%, ahead of Claude 3.7 Sonnet and DeepSeek R1.
However, in agentic coding—where AI is tested on its ability to autonomously complete multi-step software engineering tasks—Anthropic’s Claude 3.7 Sonnet outperforms all major competitors, scoring 70.3%. Gemini 2.5 Pro, at 63.8%, is competitive but falls short of Claude’s efficiency in autonomous code execution.
Factual Accuracy & Information Retrieval
Factual consistency remains a significant challenge for AI, and performance in this area varies widely. On the SimpleQA dataset, which tests an AI’s ability to provide concise and factually accurate answers, OpenAI’s GPT-4.5 leads with 62.5%, followed by Gemini 2.5 Pro at 52.9%.
OpenAI’s O3-Mini High falls far behind at 13.8%, while DeepSeek R1 scores 30.1%. These results indicate that while Gemini 2.5 Pro performs well in factual accuracy, OpenAI’s more advanced models still hold a strong advantage in ensuring information reliability.
Multimodal Reasoning & Long-Context Processing
Unlike OpenAI’s models, which currently lack full multimodal support in some benchmarks, Gemini 2.5 Pro demonstrates strong performance in vision-based reasoning. It scores 81.7% on the MMMU benchmark, a test that evaluates AI comprehension of visual data, far ahead of GPT-4.5 (74.4%) and Claude 3.7 Sonnet (75.0%).
Additionally, Google’s model is highly capable of processing long-context inputs. It achieves 91.5% accuracy on MRCR 128K, which evaluates AI retention of large text sequences, and maintains 83.1% performance at a 1 million-token scale—far superior to OpenAI’s best available long-context performance of 36.3%.
Google’s Gemini Evolution: From Bard to AI-First Integration
Gemini’s evolution is reshaping Google’s AI ecosystem. Initially launched as Bard, the transition to Gemini marked a shift toward more advanced AI reasoning and deep integration across Google’s services. This shift has only accelerated with the latest developments.
One of the biggest changes is Google’s decision to replace Google Assistant with Gemini AI, signaling its commitment to making Gemini its flagship AI assistant. Unlike Google Assistant, which relied on predefined responses, Gemini offers real-time multimodal capabilities, including screen-based AI assistance and live camera interactions via Gemini Live.
Google is also embedding Gemini AI more deeply into its productivity tools. The latest Google Drive update integrates Gemini for smart file suggestions and AI-generated summaries, improving document navigation. Meanwhile, Gmail now features AI-powered search, making email retrieval more intuitive.
Google’s expansion of NotebookLM is another step toward AI-powered knowledge management. The new Mind Maps feature, introduced in March 2025, allows users to visually organize research, complementing AI-generated notes.
The Competitive Landscape: Google vs OpenAI vs Microsoft
As AI reasoning models evolve, the competition between Google, OpenAI, and Microsoft continues to intensify. OpenAI remains a leader in factual accuracy and structured reasoning, while Google is betting on multimodal AI, personalization, and productivity integrations. Meanwhile, Microsoft is leveraging Copilot AI to rival Gemini in business applications, and Adobe is pushing AI-powered automation in creative tools.
The battle for AI-powered search assistants is also heating up. OpenAI is reportedly working on a ChatGPT-powered search experience, while Google’s latest updates allow Gemini to use search history for personalized responses. This move brings both new AI capabilities and privacy concerns, as Google aims to refine AI interactions while balancing regulatory scrutiny.
With Gemini 2.5 Pro, Google is making a strong push for advanced reasoning, multimodal AI, and deep integration into user workflows. However, challenges remain, particularly in factual consistency and agentic AI, where competitors like OpenAI and Anthropic still hold an advantage. As AI-powered assistants, search models, and productivity tools continue to evolve, the next generation of AI competition will likely center around personalization, reasoning, and real-time multimodal interaction.