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Gemini 2.5 Pro vs Gemini 3.1 Pro

Compare Gemini 2.5 Pro and Gemini 3.1 Pro side-by-side. See how these vision models stack up in Object Detection, Open Prompt, Classification, OCR, and Image Captioning.

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GoogleGemini 2.5 Pro
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Gemini 2.5 Pro vs Gemini 3.1 Pro: Overview

Gemini 2.5 Pro

Gemini 2.5 Pro, released on June 17, 2025, is Google DeepMind’s most capable model in the Gemini 2.5 family, optimized for deep reasoning, coding, and complex multimodal tasks. It accepts text, images, audio, video, and PDFs as input and outputs text. The model supports 1 million input tokens with an output capacity of up to 65K tokens, enabling large-scale comprehension of datasets, codebases, and technical documents. Its training knowledge extends to January 2025.

Pro outperforms earlier Gemini 2.0 models across benchmarks, including agentic coding tasks where it achieved ~63.8% on SWE-Bench Verified. It supports structured outputs, function calling, code execution, search grounding, and URL context, making it well-suited for enterprise, STEM, and developer workflows. However, it does not currently support image or audio generation in its stable release, and its higher computational cost and latency make it less efficient than Flash or Flash-Lite. It is available via the Gemini API, Google AI Studio, and Vertex AI.

Gemini 3.1 Pro

Gemini 3.1 Pro is a proprietary multimodal model from Google’s Gemini 3 series, released in early 2026 and designed for advanced reasoning across large multimodal datasets. It accepts text, images, audio, video, and documents, supporting up to a 1-million-token input context with up to 64k output tokens. Compared with Gemini 3 Pro, it improves long-context synthesis and multi-step reasoning, enabling more reliable analysis of large documents, datasets, and software codebases.

The model also advances visual understanding and grounding, allowing it to interpret UI screenshots, diagrams, and real-world scenes while referencing specific regions within images or video. These capabilities make Gemini 3.1 Pro well suited for multimodal workflows involving document processing, interface analysis, robotics research, and complex visual reasoning.

Gemini 2.5 Pro vs Gemini 3.1 Pro Comparison Table

PropertyGemini 2.5 ProGemini 3.1 Pro
OrganizationGoogleGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJun 2025Feb 2026
Context Window1.0M1.0M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$1.25$2.00
Output $/1M$10.00$12.00
Vision Tasks
CaptioningDemoDemo
ClassificationDemoDemo
Object DetectionDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Visual Understanding
Overall Score
70.15%
75.76%
Avg Response Time11.87s6.13s
Median input tokensincl. image tokens2941.1K
Median output tokens56511
Est. cost / taskon this benchmark$0.0060$0.0024
Defect Detection
73.3%(11/15)
73.3%(11/15)
Document Understanding
88.9%(8/9)
88.9%(8/9)
Object Counting
20%(2/10)
44.4%(4/9)
Object Understanding
78.6%(11/14)
92.9%(13/14)
Spatial Understanding
78.9%(15/19)
73.7%(14/19)
OCR
Overall Score
78.6%
89.52%
Avg Response Time4.91s3.11s
Median input tokensincl. image tokens2901.1K
Median output tokens32312
Est. cost / taskon this benchmark$0.0036$0.0024
Focused Scene OCR
78.8%(78/99)
94.9%(94/99)
Handwritten Math
80%(8/10)
90%(9/10)
License Plate Recognition
90%(27/30)
90%(27/30)
Text Recognition
73.3%(22/30)
86.7%(26/30)
VQA & Extraction
75%(45/60)
81.7%(49/60)

Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology