Gemini 3.1 Pro vs Gemini 3.5 Flash

Compare Gemini 3.1 Pro and Gemini 3.5 Flash side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, Classification, OCR, and Object Detection.

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GoogleGemini 3.1 Pro
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GoogleGemini 3.5 Flash
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Models in this comparison

Gemini 3.1 Pro vs Gemini 3.5 Flash: Overview

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 3.5 Flash

Gemini 3.5 Flash is a multimodal language model developed by Google DeepMind and released at Google I/O 2026. It is built on the Gemini 3 Flash reasoning foundation and introduces configurable thinking levels (minimal, low, medium, and high) that allow developers to tune the depth of internal reasoning before a response is generated. The model accepts text, image, video, audio, and PDF inputs and produces text output, with a 1 million token context window and up to 65,000 output tokens per request. It is natively multimodal, processing visual inputs alongside text to support tasks such as image captioning, classification, optical character recognition, object detection, and visual grounding, where the model references specific regions within an image or video frame.

Its vision capabilities extend to interpreting UI screenshots, diagrams, charts, and real-world scenes, as well as understanding video and live frame sequences for activity and scene recognition. The model supports combined tool use, including Google Search, URL context, code execution, and custom functions, within a single request, and it uses reasoning context from previous turns when thought signatures are present in the conversation history, enabling persistent multi-turn reasoning chains. Gemini 3.5 Flash carries a knowledge cutoff of January 2026 and is available via the Gemini API, Google AI Studio, Google Antigravity, and the Gemini Enterprise Agent Platform.

Gemini 3.1 Pro vs Gemini 3.5 Flash Comparison Table

PropertyGemini 3.1 ProGemini 3.5 Flash
OrganizationGoogleGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateFeb 2026May 2026
Context Window1.0M1.0M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$2.00$1.50
Output $/1M$12.00$9.00
Vision Tasks
CaptioningDemoDemo
ClassificationDemoDemo
Object DetectionDemoDemo
OCRDemoDemo
Visual Question AnsweringDemoDemo
Chart Question Answering
Document Question Answering
Multi-Label Classification
Vision Language
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation Vision
Vision Evalspass/fail results · 66 prompts
Score key:≥75%40–74%<40%
Overall Score
75.76%
79.1%
Avg Response Time6.13s6.71s
Median input tokensincl. image tokens1.1K1.1K
Median output tokens11294
Est. cost / taskon this benchmark$0.0024$0.0043
Defect Detection
73.3%(11/15)
80%(12/15)
Document Understanding
88.9%(8/9)
77.8%(7/9)
Object Counting
44.4%(4/9)
60%(6/10)
Object Understanding
92.9%(13/14)
92.9%(13/14)
Spatial Understanding
73.7%(14/19)
78.9%(15/19)

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