Gemini 3.5 Flash vs Gemma 4 12B

Compare Gemini 3.5 Flash and Gemma 4 12B side-by-side.

Compare Gemini 3.5 Flash vs Gemma 4 12B 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.

Models in this comparison

Gemini 3.5 Flash vs Gemma 4 12B: 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.

Gemma 4 12B

Gemma 4 12B is an open-weight multimodal model from Google in the Gemma 4 family. It is intended for text and image understanding tasks such as visual question answering, OCR, captioning, and document understanding, with a smaller parameter footprint than the larger Gemma 4 variants.

This entry is connected to Roboflow Playground vision evals for comparison. No runnable Playground workflow is configured yet, so the model page is used for discovery and benchmark context rather than direct hosted inference.

Gemini 3.5 Flash vs Gemma 4 12B Comparison Table

PropertyGemini 3.5 FlashGemma 4 12B
OrganizationGoogleGoogle
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateMay 2026Jun 2026
Context Window1.0M
Parameters12B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$1.50
Output $/1M$9.00
Vision Tasks
CaptioningDemo
OCRDemo
Visual Question AnsweringDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Multi-Label Classification
Object DetectionDemo
Vision Language
Model Features
Multimodal Vision
LLMs with Vision Capabilities
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Overall Score
79.1%
62.69%
Avg Response Time6.71s6.88s
Median input tokensincl. image tokens1.1K
Median output tokens294
Est. cost / taskon this benchmark$0.0043
Defect Detection
80%(12/15)
73.3%(11/15)
Document Understanding
77.8%(7/9)
88.9%(8/9)
Object Counting
60%(6/10)
10%(1/10)
Object Understanding
92.9%(13/14)
78.6%(11/14)
Spatial Understanding
78.9%(15/19)
57.9%(11/19)

Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology