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Gemma 4 12B vs Grok 4.7

Compare Gemma 4 12B and Grok 4.7 side-by-side.

Compare Gemma 4 12B vs Grok 4.7 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 4.7 Comparison Table

Evals updated October 13, 2026Pricing updated October 17, 2026

PropertyGemma 4 12BGrok 4.7
OrganizationGoogleSpaceXAI
Categoryopenclosed
Modalitymultimodal—
Release DateJun 2026Sep 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 VisionSupportedNot listed
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
OverallNot evaluated
63.5%
Avg cost / sample–$0.020
Avg speed / sample–33.31s
By task
Object Detection (low)–
40.4%
±0.6, Mean of 3 runs, range 39.8 to 41.0
$0.021
Object Detection (high)–
41.2%
±1.6, Mean of 3 runs, range 39.6 to 42.8
$0.028
Counting (low)–
61.7%
±1.3, Mean of 3 runs, range 60.8 to 63.5
$0.011
Counting (high)–
60.8%
±1.3, Mean of 3 runs, range 59.5 to 62.2
$0.017
Identification (low)–
87.5%
±3.1, Mean of 3 runs, range 84.4 to 90.6
$0.0063
Identification (high)–
80.2%
±1.6, Mean of 3 runs, range 78.1 to 81.3
$0.0093
OCR–
63.6%
$0.023
by category
Single value
54.4%
Transcription
89.5%
Structured JSON
86.4%
Text localization
14.8%
Reasoning (low)–
64.2%
±2.3, Mean of 3 runs, range 62.3 to 66.9
$0.015
Reasoning (high)–
66.9%
±1.3, Mean of 3 runs, range 65.6 to 68.2
$0.024

Gemma 4 12B vs Grok 4.7: 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 4.7

Grok 4.7 is a proprietary multimodal reasoning model from SpaceXAI that accepts images alongside text and returns text-only output. On visual inputs it supports image captioning, visual question answering, OCR, document and chart question answering, and image classification and tagging, with all results expressed as generated text rather than bounding boxes or masks. Its 500,000 token context window leaves room for several images, long documents, or extended conversations about visual content in a single request.

The model exposes a configurable reasoning effort setting with low, medium, high, and xhigh levels (high by default), letting callers trade latency for the amount of deliberation spent on a prompt, including multi-step questions about an image. Built on a larger base model than Grok 4.6 with extended reinforcement learning on harder tasks, it works longer on difficult problems and checks its own work more carefully at the same serving speed. SpaceXAI's launch materials focus on coding and agentic knowledge work and report no image benchmark results.

Frequently Asked Questions

Gemma 4 12B has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.

Gemma 4 12B is released under Apache 2.0, while Grok 4.7 uses Proprietary. In practice: Gemma 4 12B — free for commercial use; Grok 4.7 — commercial use per vendor terms. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.