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Gemini 3.1 Pro vs Gemini 2.5 Pro

Compare Gemini 3.1 Pro and Gemini 2.5 Pro across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.

Overview ↓ Pricing ↓ Capabilities ↓ Benchmarks ↓ Community ↓ Tools ↓ Verdict ↓ FAQ ↓ Related ↓

Overview Comparison

Structured side-by-side differences for the highest-signal model metadata.

Gemini 3.1 Pro
Gemini 2.5 Pro

Provider

The entity that currently provides this model.

Gemini 3.1 Pro Google
Gemini 2.5 Pro Google

Model ID

The routed model identifier exposed by upstream providers.

Gemini 3.1 Pro google/gemini-3.1-pro-preview
Gemini 2.5 Pro google/gemini-2.5-pro

Input Context Window

The number of tokens supported by the input context window.

Gemini 3.1 Pro 1,048,576 tokens
Gemini 2.5 Pro 1,048,576 tokens

Maximum Output Tokens

The number of tokens that can be generated by the model in a single request.

Gemini 3.1 Pro 65,536 tokens tokens
Gemini 2.5 Pro 65,536 tokens tokens

Open Source

Whether the model's code is available for public use.

Gemini 3.1 Pro No
Gemini 2.5 Pro No

Release Date

When the model was first released.

Gemini 3.1 Pro Feb 19, 2026
Gemini 2.5 Pro Jun 17, 2025

Knowledge Cut-off Date

When the model's knowledge was last updated.

Gemini 3.1 Pro February 2026
Gemini 2.5 Pro 2025-01-31

API Providers

The providers that currently expose the model through an API.

Gemini 3.1 Pro
Google, OpenRouter, Vertex AI, Gemini API
Gemini 2.5 Pro
Google, Gemini API

Modalities

Types of data each model can process or return.

Gemini 3.1 Pro
Text Image File Audio Video Code
Gemini 2.5 Pro
Text Image File Audio Video Code

Pricing Comparison

Compare current token pricing before you choose the cheaper or more scalable API option.

Gemini 3.1 Pro Google
Input price $2.00 Per 1M tokens
Output price $12.00 Per 1M tokens
Gemini 2.5 Pro Google
Input price $1.25 Per 1M tokens
Output price $10.00 Per 1M tokens

Capabilities Comparison

See where each model overlaps, where they differ, and which one supports more of the features you care about.

Capability
Gemini 3.1 Pro
Gemini 2.5 Pro
Agentic Task Execution Supports autonomous, long-horizon task execution with improved tool orchestration and stability, suited for structured domains like finance and spreadsheet workflows.
Gemini 3.1 Pro Supported
Gemini 2.5 Pro —
Code Generation Produces and analyzes code across multiple programming languages, with measurable gains on SWE benchmarks and real-world software engineering environments.
Gemini 3.1 Pro Supported
Gemini 2.5 Pro Supported
Configurable Thinking Offers a medium thinking level setting that allows users to tune the trade-off between reasoning depth, response speed, and token cost per request.
Gemini 3.1 Pro Supported
Gemini 2.5 Pro —
Extended Context Window Processes up to 1,048,576 tokens in a single context, enabling analysis of large documents, codebases, or long conversation histories without truncation.
Gemini 3.1 Pro —
Gemini 2.5 Pro Supported
File
Gemini 3.1 Pro Supported
Gemini 2.5 Pro Supported
Image
Gemini 3.1 Pro Supported
Gemini 2.5 Pro Supported
Long Context Window Processes up to 1,048,576 tokens in a single request, enabling analysis of entire codebases, lengthy documents, or extended multi-turn conversations without truncation.
Gemini 3.1 Pro Supported
Gemini 2.5 Pro —
Math and STEM Analysis Handles complex mathematical reasoning and science problems, with benchmark performance cited across math and science evaluation suites.
Gemini 3.1 Pro —
Gemini 2.5 Pro Supported
Multi-Step Reasoning Applies structured reasoning chains to complex problems, achieving a 77.1% score on the ARC-AGI-2 benchmark across logic, planning, and inference tasks.
Gemini 3.1 Pro Supported
Gemini 2.5 Pro —
Multimodal Input Accepts and reasons over text, images, video, audio, and code within a single unified model, without requiring separate specialized models per modality.
Gemini 3.1 Pro Supported
Gemini 2.5 Pro Supported
Reasoning
Gemini 3.1 Pro Supported
Gemini 2.5 Pro Supported
Structured Output
Gemini 3.1 Pro Supported
Gemini 2.5 Pro Supported
Structured Reasoning Uses a thinking approach to work through multi-step problems, drawing logical conclusions before producing a final response rather than generating output directly.
Gemini 3.1 Pro —
Gemini 2.5 Pro Supported
Text
Gemini 3.1 Pro Supported
Gemini 2.5 Pro Supported
Tool Use Accepts tool definitions as inputs and can invoke external functions or APIs during a response, enabling integration with custom workflows and data sources.
Gemini 3.1 Pro Supported
Gemini 2.5 Pro Supported
Tools
Gemini 3.1 Pro Supported
Gemini 2.5 Pro Supported
Video
Gemini 3.1 Pro Supported
Gemini 2.5 Pro Supported

Benchmark Comparison

Shared benchmark rows make it easier to compare performance where both models have published scores.

Benchmark Gemini 3.1 Pro Gemini 2.5 Pro
AIME 2024
American math olympiad problems
Gemini 3.1 Pro N/A
Gemini 2.5 Pro 88.7%
ARC-AGI-2
Novel abstract reasoning and pattern recognition
Gemini 3.1 Pro 77.1%
Gemini 2.5 Pro N/A
BrowseComp
Complex web browsing and information retrieval
Gemini 3.1 Pro 85.9%
Gemini 2.5 Pro N/A
GPQA Diamond
PhD-level science questions (biology, physics, chemistry)
Gemini 3.1 Pro 94.1%
Gemini 2.5 Pro 84.4%
HLE
Questions that challenge frontier models across many domains
Gemini 3.1 Pro 44.7%
Gemini 2.5 Pro 21.1%
LiveCodeBench
Real-world coding tasks from recent competitions
Gemini 3.1 Pro N/A
Gemini 2.5 Pro 80.1%
MATH-500
Undergraduate and competition-level math problems
Gemini 3.1 Pro N/A
Gemini 2.5 Pro 96.7%
MCP-Atlas Tool Use
Structured tool use via Model Context Protocol
Gemini 3.1 Pro 69.2%
Gemini 2.5 Pro N/A
MMLU-Pro
Expert knowledge across 14 academic disciplines
Gemini 3.1 Pro N/A
Gemini 2.5 Pro 86.2%
MMMLU
Multilingual and multimodal understanding
Gemini 3.1 Pro 92.6%
Gemini 2.5 Pro N/A
SciCode
Scientific research coding and numerical methods
Gemini 3.1 Pro 58.9%
Gemini 2.5 Pro 42.8%
SWE-bench Pro
Challenging real-world software engineering tasks
Gemini 3.1 Pro 54.2%
Gemini 2.5 Pro N/A
SWE-bench Verified
Real GitHub issues requiring multi-file code fixes
Gemini 3.1 Pro 80.6%
Gemini 2.5 Pro N/A
Terminal-Bench 2.0
Agentic coding and terminal command tasks
Gemini 3.1 Pro 68.5%
Gemini 2.5 Pro N/A
τ²-bench Retail
Agentic tool use in retail scenarios
Gemini 3.1 Pro 90.8%
Gemini 2.5 Pro N/A
τ²-bench Telecom
Agentic tool use in telecom scenarios
Gemini 3.1 Pro 99.3%
Gemini 2.5 Pro N/A
Community discussion

What Reddit discussions say about Gemini 3.1 Pro vs Gemini 2.5 Pro

Gemini 3.1 Pro and Gemini 2.5 Pro are both surfacing live Reddit discussions, giving this comparison a community layer beyond specs and benchmarks.

The most visible threads right now are clustered in r/singularity, r/Bard, r/GeminiAI.

Gemini 2.5 Pro r/singularity 1,049 upvotes 114 comments December 15, 2025
Google just dropped a new Agentic Benchmark: Gemini 3 Pro beat Pokémon Crystal (defeating Red) using 50% fewer tokens than Gemini 2.5 Pro.

I just saw this update drop on X from Google AI Studio. They benchmarked **Gemini 3 Pro** against **Gemini 2.5 Pro** on a full run of **Pokémon Crystal** (which is significantly longer/harder than the standard Pokemon Red benchmark).

**The Results:**

**Completion:** It obtained all 16 badges and defeated the hidden boss Red (the hardest challenge in the game).

**Efficiency:** It accomplished this using **roughly half the tokens and turns** of the previous model (2.5 Pro).

This is a huge signal for **Agentic Efficiency.** Halving the token usage for a long-horizon task means the model isn't just **faster** ,it's making better decisions with less "flailing" or trial and error. It implies a massive jump in planning capability.

**Source: Google Ai studio( X article)**

🔗: https://x.com/i/status/2000649586847985985

Open Reddit thread
View more discussions →

AI tools related to Gemini 3.1 Pro vs Gemini 2.5 Pro

These tools are closely connected to one or both models in this comparison and can help you evaluate real-world fit.

AI Image Enhancer

BeautyPlus

BeautyPlus: BeautyPlus is an AI-powered online platform offering a comprehensive suite of image and video editing tools. It features an AI Image Enhancer to improve photo quality, resolution, color, and contrast, and includes advanced functionalities like blurry photo correction, noise reduction, and blemish minimization. Additionally, it integrates Nano Banana Pro, an AI image generator and editor powered by Google Gemini 3 Pro, enabling users to generate images from text, edit existing images with prompts, and combine elements from multiple images. The platform also provides various other tools such as background removers, object removers, AI filters, video enhancers, and more, catering to both professional and casual users for diverse creative needs.

1 visits
Large Language Models (LLMs)

O.Translator

O.Translator is an AI-powered online translation platform designed to translate documents while maintaining their original formatting. It supports a wide range of file types, including PDF, DOCX, XLSX, PPTX, and EPUB. The service provides high-accuracy AI translations, easy editing tools, free previews, cost-effective pricing, data privacy, and team-based translation features.

Free 0 visits 14 saves
Large Language Models (LLMs)

Diagramming AI

Diagramming AI is an AI-powered platform designed to simplify the creation, editing, and discussion of complex UML diagrams and workflows. Users can generate professional-grade diagrams by describing their vision, while the AI handles the technical implementation. Key features include automated diagram generation, an AI chat interface for real-time edits and suggestions, error resolution, a visual editor with Excalidraw integration, and project-based storage for Mermaid, PlantUML, Graphviz, and Excalidraw code.

Free 35 visits 2 saves
Large Language Models (LLMs)

googlegemini.co

googlegemini.co is a free tool for interacting with text and images, powered by the Google Gemini Pro API. It allows you to use Gemini easily without managing your own server or API configurations. Google Gemini is a multimodal AI developed by DeepMind capable of processing text, audio, images, and more. It is optimized for various devices, performs well on AI benchmarks, and is built with a focus on safety and responsible AI practices.

Free 0 visits 2 saves

Which model should you choose?

Use the summary below to decide which model better fits your workflow, budget, and feature requirements.

Best fit for

Gemini 3.1 Pro

Gemini 3.1 Pro is a stronger fit for long-context workloads, reasoning-heavy tasks, tool-augmented workflows.

Best fit for

Gemini 2.5 Pro

Gemini 2.5 Pro is a stronger fit for long-context workloads, reasoning-heavy tasks, tool-augmented workflows.

Verdict

Choose Gemini 3.1 Pro if you prioritize long-context workloads, reasoning-heavy tasks, tool-augmented workflows. Choose Gemini 2.5 Pro if your workflow depends more on long-context workloads, reasoning-heavy tasks, tool-augmented workflows.

FAQ

Common questions about Gemini 3.1 Pro vs Gemini 2.5 Pro

What is the main difference between Gemini 3.1 Pro and Gemini 2.5 Pro?

Gemini 3.1 Pro leans toward long-context workloads, reasoning-heavy tasks, tool-augmented workflows, while Gemini 2.5 Pro is better suited to long-context workloads, reasoning-heavy tasks, tool-augmented workflows.

Which model is cheaper: Gemini 3.1 Pro or Gemini 2.5 Pro?

Gemini 2.5 Pro starts lower on input pricing at $1.2500 per 1M input tokens, compared with $2.0000 for Gemini 3.1 Pro.

Which model has the larger context window: Gemini 3.1 Pro or Gemini 2.5 Pro?

Gemini 3.1 Pro is listed with a context window of 1,048,576, while Gemini 2.5 Pro is listed with 1,048,576.

How should I evaluate Gemini 3.1 Pro vs Gemini 2.5 Pro for my use case?

This comparison currently includes 16 shared benchmark rows, helping you compare practical performance across overlapping evaluations.