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Gemini 3.5 Flash vs Gemini 3 Flash

Compare Gemini 3.5 Flash and Gemini 3 Flash side-by-side. See how these vision models stack up in Open Prompt, Image Captioning, OCR, Classification, and Object Detection.

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GoogleGemini 3.5 Flash
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Gemini 3.5 Flash vs Gemini 3 Flash on Vision Evals

Gemini 3.5 Flash scores higher on 5 of the six Vision Evals tasks.

The widest gap is Object Detection, where Gemini 3.5 Flash leads 68.7% to 38.6%.

Overall, Gemini 3.5 Flash averages 86.6% (#1 of 25) against 74.9% (#10 of 25) for Gemini 3 Flash.

Gemini 3 Flash is both cheaper ($0.0021 vs $0.011 per sample) and faster (4.1s vs 5.8s per sample).

Gemini 3.5 FlashGemini 3 Flash

Gemini 3.5 Flash vs Gemini 3 Flash Comparison Table

Evals updated August 6, 2026Pricing updated August 7, 2026

PropertyGemini 3.5 FlashGemini 3 Flash
OrganizationGoogleGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateMay 2026Dec 2025
Context Window1.0M1.0M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$1.50$0.500
Output $/1M$9.00$3.00
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemoDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
86.6%
74.9%
Avg cost / sample$0.011$0.0021
Avg speed / sample5.82s4.10s
By task
Object Detection
68.7%
$0.016
38.6%
$0.0031
Counting
81.1%
$0.0075
67.6%
$0.0012
Identification
100.0%
$0.0042
93.8%
$0.0009
OCR
91.1%
$0.016
87.6%
$0.0024
Data Extraction
94.8%
$0.0037
96.9%
$0.0008
Reasoning (low)
84.1%
$0.0080
64.9%
$0.0020
Reasoning (high)
82.8%
$0.017
74.2%
$0.0040

Gemini 3.5 Flash vs Gemini 3 Flash: Overview

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 Flash

Gemini 3 Flash is a proprietary multimodal large language model developed by Google through Google DeepMind, designed to deliver fast, cost-efficient reasoning across real-time products and developer workflows. Released in December 2025, it is the Flash-tier variant of the Gemini 3 family, balancing low latency with reasoning quality approaching Pro models.

The model supports text, images, audio, and video, with an exceptionally large context window of roughly one million input tokens and outputs up to ~65k tokens. It emphasizes rapid responses for coding, summarization, analysis, and agentic tasks, and exposes configurable “thinking levels” via API to trade speed for deeper reasoning. Today, Gemini 3 Flash positions itself as a high-throughput, production-ready model, serving as the default in the Gemini app and Google Search’s AI Mode, optimized for scalable, interactive AI applications.