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Gemini 3.5 Flash-Lite vs Gemini 3 Flash

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

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GoogleGemini 3.5 Flash-Lite
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Gemini 3.5 Flash-Lite vs Gemini 3 Flash Comparison Table

Evals updated July 10, 2026Pricing updated July 21, 2026

PropertyGemini 3.5 Flash-LiteGemini 3 Flash
OrganizationGoogleGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJul 2026Dec 2025
Context Window1.0M1.0M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.500
Output $/1M$3.00
Vision Tasks
CaptioningDemoDemo
ClassificationDemoDemo
Object DetectionDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Document Question Answering
Multi-Label Classification
Video Classification
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation Vision
Real-Time Vision
Vision Evalsground-truth scores across 6 vision tasks
OverallNot evaluated
77.2%
Object Detection
39.3%
Counting
67.6%
Identification
93.8%
OCR
87.6%
Data Extraction
96.9%
Reasoning
78.3%
Avg cost / sample$0.0017
Avg speed / sample3.9s

Gemini 3.5 Flash-Lite vs Gemini 3 Flash: Overview

Gemini 3.5 Flash-Lite

Gemini 3.5 Flash-Lite is a natively multimodal reasoning model developed by Google DeepMind, released on July 21, 2026 as part of the Gemini 3.5 model family. It is the fastest model in the 3.5 series, designed for both low-latency tasks and high-throughput production workloads such as agentic search, document processing, receipt translation, and large-scale data extraction. The model accepts text, images, audio, and video as inputs, with a context window of up to 1 million tokens, and produces text output. It supports configurable thinking levels, allowing developers to tune the balance between response quality, cost, and latency depending on workload requirements.

On agentic and coding benchmarks, Gemini 3.5 Flash-Lite significantly outperforms its predecessor, Gemini 3.1 Flash-Lite, including on Terminal-Bench 2.1 (54% vs. 31%), GDM-MRCR v2 long-context (72.2% vs. 60.1%), and real-world task execution as measured by GDPval-AA v2 (1140 vs. 642). It also surpasses Gemini 3 Flash on SWE-Bench Pro (54.2% vs. 49.6%) and OSWorld-Verified (74.0% vs. 65.1%). According to the Artificial Analysis Index, the model generates output at approximately 350 tokens per second. It is built on the Gemini 3.5 Flash foundation and is evaluated across reasoning, coding, multimodal understanding, multilingual performance, and long-context tasks. The model is developed under Google's Frontier Safety Framework.

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.

Frequently Asked Questions

Gemini 3.5 Flash-Lite has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.

Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.