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Gemini 3 Flash vs Gemma 3 12B

Compare Gemini 3 Flash and Gemma 3 12B side-by-side. See how these vision models stack up in Open Prompt, OCR, and Image Captioning.

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GoogleGemini 3 Flash
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Gemini 3 Flash vs Gemma 3 12B Comparison Table

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

PropertyGemini 3 FlashGemma 3 12B
OrganizationGoogleGoogle
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateDec 2025Mar 2025
Context Window1.0M128K
Parameters12B
LicenseProprietaryCustom
Pricing per 1M tokens
Input $/1M$0.500$0.050
Output $/1M$3.00$0.150
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Multi-Label Classification
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Object DetectionDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
74.9%
Not evaluated
Avg cost / sample$0.0021
Avg speed / sample4.10s
By task
Object Detection
38.6%
$0.0031
Counting
67.6%
$0.0012
Identification
93.8%
$0.0009
OCR
87.6%
$0.0024
Data Extraction
96.9%
$0.0008
Reasoning (low)
64.9%
$0.0020
Reasoning (high)
74.2%
$0.0040

Gemini 3 Flash vs Gemma 3 12B: Overview

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.

Gemma 3 12B

Gemma 3 12B, announced by Google DeepMind on March 12, 2025, is part of the open-weight Gemma 3 family, designed to provide a balance between capability and accessibility. With around 12 billion parameters, it supports multimodal input (text + images) and outputs text, making it useful for reasoning, summarization, Q&A, and visual understanding tasks. The model supports an input context of 128,000 tokens and typically generates up to ~8,000 tokens in output.

The 12B variant is instruction-tuned (“Gemma-3-12B-IT”) and optimized for multilingual use across more than 140 languages. It can run on a single GPU or TPU, offering a lighter compute footprint than very large proprietary models, while still achieving strong performance in reasoning benchmarks. Quantized and lower-precision variants are available to improve efficiency. Limitations include smaller output lengths relative to input capacity, scaling hardware needs at larger sizes, and performance below massive proprietary models on the most complex multimodal or reasoning-heavy tasks.