Overview

 It sits in the Gemini 2.5 series and is meant to balance power and cost for developers and businesses. According to an Analytics Vidhya overview, this Pro‑tier model delivers higher accuracy on language and multimodal tasks, improved computational efficiency, and stronger coding and reasoning capabilities compared with Gemini 1.5 Proanalyticsvidhya.com. The model’s multimodal design lets it accept text, images, video, audio and even code repositoriesanalyticsvidhya.com. It includes a 1 million‑token context window and will eventually support up to 2 million tokensanalyticsvidhya.com. A long context and extended output allow the model to handle large documents, whole codebases or long transcripts in a single conversationventurebeat.com. The model also has an expanded knowledge base with a training cutoff in January 2025analyticsvidhya.com.

Gemini 2.5 Pro is available via Google AI Studio and the Gemini web/app interface. Developers can select the model from a drop‑down menu in Google AI Studio and upload documents, video links or audio clips; Gemini Advanced subscribers can choose the 2.5 Pro model on the Gemini websiteanalyticsvidhya.com.

Key features

• Multimodality – handles text, images, video, audio and code; supports uploads from Google Drive and direct camera or audio recordingsanalyticsvidhya.com.

• Reasoning system – uses a step‑by‑step reasoning process to produce more accurate and context‑aware outputsanalyticsvidhya.com; in practice, it shows its thought process in numbered steps, breaking down puzzles and filling tables before producing the final answeranalyticsvidhya.com.

• 1 M‑token context window – processes long inputs and generates extended outputsanalyticsvidhya.comventurebeat.com.

• Enhanced coding performance – improved code generation and analysisanalyticsvidhya.com; early hands‑on tests show it can modify whole codebases and create features efficientlyventurebeat.com.

• Up‑to‑date knowledge – training data updated through January 2025analyticsvidhya.com.

Comparison with similar models

The table below contrasts Gemini 2.5 Pro with OpenAI’s ChatGPT o‑series (GPT‑4o) based on Zapier’s mid‑2025 comparisonzapier.com and other sources.

Pros and cons

Pros

• Handles complex, multimodal tasks – can reason over text, images and video simultaneouslyanalyticsvidhya.com.

• Excellent for long‑form projects – 1 M‑token context window enables deep codebase analysis and extended conversationsventurebeat.com.

• Detailed reasoning trace – displays its thought process step‑by‑step, which helps users understand and guide the modelanalyticsvidhya.com.

• Improved coding performance – early tests show it can efficiently modify entire codebasesventurebeat.com.

Cons

• Manual memory – it doesn’t automatically remember prior conversations or user preferenceszapier.com.

• Limited voice mode – voice interaction is available only on mobile deviceszapier.com.

• Unknown final pricing – the experimental model is free, but the final cost for developers is still unannouncedventurebeat.com.

• Image generation still evolving – early tests report realistic images but with occasional minor issuesanalyticsvidhya.com.

Verdict

Gemini 2.5 Pro demonstrates how fast AI models are improving. Its huge context window, multimodal abilities and transparent reasoning make it a strong tool for developers who need to analyze large documents, codebases or mixed‑media data. While features like memory and voice interaction trail behind competitors such as ChatGPT, Gemini’s broad input support and long‑form reasoning show clear advantages. Developers who work within the Google ecosystem or who need to handle large multimodal datasets should watch this model closely.