Roboflow

Gemini 3.5 Flash-Lite vs SAM 3

Compare Gemini 3.5 Flash-Lite and SAM 3 side-by-side. See how these vision models stack up in Object Detection.

Compare Gemini 3.5 Flash-Lite vs SAM 3 live

Run the same image across every model that supports a task and compare their outputs side-by-side.

Detect and compare bounding boxes across models on the same image.

Open Object Detection in the full playground
GoogleGemini 3.5 Flash-Lite
Run to compare this model.
MetaSAM 3
Run to compare this model.

Models in this comparison

Meta

Gemini 3.5 Flash-Lite vs SAM 3 Comparison Table

Evals updated August 6, 2026Pricing updated August 10, 2026

PropertyGemini 3.5 Flash-LiteSAM 3
OrganizationGoogleMeta
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateJul 2026Nov 2025
Context Window1.0M
Parameters
LicenseProprietaryCustom
Pricing per 1M tokens
Input $/1M$0.300
Output $/1M$2.50
Vision Tasks
Object DetectionDemoDemo
CaptioningDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Instance Segmentation
Multi-Label Classification
OCRDemo
Open Vocabulary Object Detection
Promptable Concept SegmentationDemo
Video Classification
Video Object Tracking
Vision Language
Visual Question AnsweringDemo
Zero Shot Segmentation
Model Features
Foundation Vision
Multimodal Vision
LLMs with Vision Capabilities
Zero-shot Detection
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
69.6%
Not evaluated
Avg cost / sample$0.0014
Avg speed / sample2.70s
By task
Object Detection
57.5%
$0.0023
Counting
52.7%
$0.0007
Identification
81.3%
$0.0004
OCR
87.4%
$0.0011
Data Extraction
90.7%
$0.0004
Reasoning (low)
48.3%
$0.0012
Reasoning (high)
68.9%
$0.0042

Gemini 3.5 Flash-Lite vs SAM 3: 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.

SAM 3

Released on November 19th, 2025, Segment Anything 3 (SAM 3) is a zero-shot image segmentation model that “detects, segments, and tracks objects in images and videos based on concept prompts.” This model was developed by Meta as the third model in the Segment Anything series.

Unlike its previous SAM models (Segment Anything and Segment Anything 2), you can provide SAM 3 with the prompt “shipping container” and it will generate precise segmentation masks for all shipping containers in an image. SAM 3 generates segmentation masks that correspond to the location of the objects found with a text prompt.

Frequently Asked Questions

SAM 3 has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.

Gemini 3.5 Flash-Lite is released under Proprietary, while SAM 3 uses Custom. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.

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