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Gemini 3.5 Flash-Lite vs Moondream 2

Compare Gemini 3.5 Flash-Lite and Moondream 2 side-by-side.

Compare Gemini 3.5 Flash-Lite vs Moondream 2 live

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

These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.

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Gemini 3.5 Flash-Lite vs Moondream 2 Comparison Table

Evals updated September 5, 2026Pricing updated September 21, 2026

PropertyGemini 3.5 Flash-LiteMoondream 2
OrganizationGoogleMoondream
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateJul 2026Jan 2024
Context Window1.0M
Parameters~2B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$0.300
Output $/1M$2.50
Vision Tasks
CaptioningDemo
Object DetectionDemo
Vision Language
Visual Question AnsweringDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Multi-Label Classification
OCRDemo
Video Classification
Model Features
Multimodal Vision
Foundation Vision
LLMs with Vision Capabilities
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
70.3%
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
84.4%
$0.0004
OCR
87.4%
$0.0011
Data Extraction
91.8%
$0.0004
Reasoning (low)
48.3%
$0.0012
Reasoning (high)
68.9%
$0.0042

Gemini 3.5 Flash-Lite vs Moondream 2: 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.

Moondream 2

Moondream 2 is a small open-source vision-language model from Moondream, the company founded by Vikhyat Korrapati. It was first released in early 2024 and updated through mid-2025. At approximately 1.9 billion parameters, it is designed to run efficiently on consumer hardware such as laptops and edge devices while supporting a practical range of multimodal tasks. Moondream 2 combines a vision encoder based on SigLIP with a compact language backbone, trained for image understanding tasks rather than as a general chat model.

The model accepts an image paired with a natural language prompt and produces text responses, supporting visual question answering, image captioning, and image-conditioned dialogue. Later Moondream 2 releases added object localization through a point API that returns coordinates for queried objects, along with improvements to OCR, counting, and document understanding. Moondream 2 is distributed under the Apache 2.0 license and is available through Hugging Face and the maintainer's distribution. Because the model is updated frequently, production deployments should pin to a specific revision rather than tracking the latest release. A successor model, Moondream 3 (Preview), was released in September 2025 with a 9B mixture-of-experts architecture and 2B active parameters, offering substantially stronger visual reasoning than Moondream 2 while retaining the efficiency-focused design. A referring expression segmentation extension to Moondream 3 was released in March 2026.