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Gemma 4 12B vs Grok 4.6

Compare Gemma 4 12B and Grok 4.6 side-by-side.

Compare Gemma 4 12B vs Grok 4.6 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

Gemma 4 12B vs Grok 4.6 Comparison Table

Evals updated October 13, 2026Pricing updated October 23, 2026

PropertyGemma 4 12BGrok 4.6
OrganizationGoogleSpaceXAI
Categoryopenclosed
Modalitymultimodalmultimodal
Release DateJun 2026Aug 2026
Context Window—500K
Parameters12BUnknown
LicenseApache 2.0Proprietary
Commercial usefree for commercial usecommercial use per vendor terms
Pricing per 1M tokens
Input $/1MNo published price$2.00
Output $/1MNo published price$6.00
Vision Tasks
CaptioningSupportedDemo
OCRSupportedDemo
Vision LanguageSupportedSupported
Visual Question AnsweringSupportedDemo
Chart Question AnsweringNot listedSupported
ClassificationNot listedDemo
Document Question AnsweringNot listedSupported
Image TaggingNot listedSupported
Multi-Label ClassificationNot listedSupported
Object DetectionNot listedDemo
Model Features
Multimodal VisionSupportedSupported
Foundation VisionNot listedSupported
LLMs with Vision CapabilitiesNot listedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
OverallNot evaluated
59.1%
Avg cost / sample–$0.011
Avg speed / sample–19.32s
By task
Object Detection (low)–
23.8%
±2.8, Mean of 3 runs, range 20.2 to 25.9
$0.013
Object Detection (high)–
24.0%
±1.0, Mean of 3 runs, range 23.1 to 25.1
$0.041
Counting (low)–
65.8%
±4.1, Mean of 3 runs, range 62.2 to 70.3
$0.0079
Counting (high)–
56.8%
±1.4, Mean of 3 runs, range 55.4 to 58.1
$0.027
Identification (low)–
84.4%
±3.1, Mean of 3 runs, range 81.3 to 87.5
$0.0055
Identification (high)–
85.4%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.015
OCR (low)–
60.6%
$0.011
by category
Single value
50.0%
Transcription
89.0%
Structured JSON
84.4%
Text localization
11.0%
OCR (high)–
61.2%
$0.030
by category
Single value
50.9%
Transcription
88.7%
Structured JSON
85.7%
Text localization
9.4%
Reasoning (low)–
61.1%
±1.3, Mean of 3 runs, range 59.6 to 62.3
$0.0093
Reasoning (high)–
63.8%
±2.0, Mean of 3 runs, range 62.3 to 66.2
$0.032

Gemma 4 12B vs Grok 4.6: Overview

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.

Grok 4.6

Grok 4.6 is a proprietary reasoning model from xAI aimed at long-running agentic workflows, coding, and knowledge work. It accepts text and image input and returns text, with a 500,000 token context window and a knowledge cutoff of February 1, 2026. The model exposes an adjustable reasoning budget with low, medium, high, and xhigh settings, where high is the default, and it supports function calling, structured outputs, web and X search, and code execution as documented tool behaviors. Its visual capability covers interpreting images supplied alongside text prompts, which places it in the visual question answering and document understanding family, and it can also return object detection boxes as text coordinates when prompted.

xAI characterizes Grok 4.6 as the result of an extended post-training run over the Grok 4.5 lineage rather than a new pretrained base. The described recipe combines curated model-generated reasoning and technical data, engineering data, a revised optimizer, regenerated supervised fine-tuning trajectories, and reinforcement learning across agent environments spanning knowledge work, coding, kernel optimization, web development, and computer-aided design. Parameter count and architecture specifics are not disclosed. Independent measurement from Artificial Analysis places the model at 61 on its Intelligence Index, five points above Grok 4.5.