Google's Gemini 2.5 Pro Surpasses Rivals in Coding, Mathematics, and Science

Google's Gemini 2.5 Pro Surpasses Rivals in Coding, Mathematics, and Science

The latest AI model from Google, Gemini 2.5 Pro, sets a new benchmark in reasoning-based artificial intelligence, outperforming leading models from OpenAI, Anthropic, and DeepSeek across multiple critical areas.

A Leap in AI Reasoning

Google has officially introduced Gemini 2.5 Pro, the first release in the Gemini 2.5 series. This advanced multimodal reasoning model demonstrates superior performance over its competitors, particularly in fields such as coding, mathematics, and science, according to industry-standard evaluations.

Understanding Reasoning AI Models

Reasoning-based AI models are designed to methodically analyze information before generating responses. These models meticulously evaluate contextual details, cross-check facts, and ensure logical coherence, though these enhanced capabilities come at the cost of higher computational demand and increased operational expenses.

OpenAI pioneered the concept of reasoning models with the introduction of o1 last September, a departure from its earlier GPT models focused primarily on language generation. This innovation spurred competition, leading to releases like DeepSeek’s R1, Anthropic’s Claude Sonnet 3.7, and xAI’s Grok 3.

Moving Beyond 'Flash Thinking'

Google first ventured into reasoning AI with Gemini 2.0 Flash Thinking in December. Originally designed for dynamic agent-based applications, Flash Thinking was enhanced to support file uploads and accommodate larger prompts. However, with the launch of Gemini 2.5 Pro, Google appears to be phasing out the "Thinking" branding altogether.

In an official announcement regarding Gemini 2.5, Google indicated that reasoning capabilities will now be embedded as a fundamental component in all upcoming AI models. This marks a transition toward a more unified AI framework, eliminating the need for separate branding to highlight cognitive functionalities.

The experimental model boasts "a significantly enhanced base model" coupled with "improved post-training." Google highlights its leading position on the LMArena leaderboard, where it ranks as a top performer across diverse AI tasks.

Setting New Standards in Science, Mathematics, and Programming

Gemini 2.5 Pro excels in academic evaluation metrics, achieving an 86.7% score on the AIME 2025 mathematics test and 84.0% on the GPQA diamond benchmark for scientific reasoning. Additionally, on Humanity’s Last Exam—a comprehensive assessment covering mathematics, science, and humanities—the model leads with an 18.8% score.

Remarkably, these results were obtained without relying on high-cost test-time learning strategies, a technique used by models like o1 and R1 to adapt during evaluation.

In the realm of software development, Gemini 2.5 Pro exhibits a mix of strengths. It achieves a 68.6% score on the Aider Polyglot benchmark for code editing, surpassing many of its peers. However, it falls slightly behind Claude Sonnet 3.7 in broader programming tasks, securing a 63.8% rating on SWE-bench Verified.

Despite this, Google asserts that Gemini 2.5 Pro "excels at creating visually compelling web apps and agentic code applications," demonstrating its capabilities by generating an entire video game from a single prompt.

Expanding Contextual Understanding

The model supports an extensive context window of one million tokens, equating to processing up to 750,000 words in a single prompt—roughly the length of the first six books in the Harry Potter series. Google has announced plans to further expand this limit to two million tokens in the near future.

Currently, Gemini 2.5 Pro is accessible through the Gemini Advanced app, available via a $20 monthly subscription. Additionally, developers and enterprises can integrate the model via Google AI Studio. In the coming weeks, it will also be available on Vertex AI, Google’s machine-learning platform, with detailed pricing structures set to be revealed soon.