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Gemini 3.6 Flash vs Grok 4.6

Compare Gemini 3.6 Flash and Grok 4.6 side-by-side. See how these vision models stack up in Open Prompt, Classification, Image Captioning, OCR, and Object Detection.

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GoogleGemini 3.6 Flash
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GrokGrok 4.6
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Models in this comparison

Gemini 3.6 Flash vs Grok 4.6 on Vision Evals

Gemini 3.6 Flash scores higher on 5 of the six Vision Evals tasks.

The widest gap is Object Detection, where Gemini 3.6 Flash leads 58.9% to 23.8%.

Overall, Gemini 3.6 Flash averages 83.3% (#10 of 61) against 68.7% (#33 of 61) for Grok 4.6.

Gemini 3.6 Flash is both cheaper ($0.0032 vs $0.0097 per sample) and faster (14.7s vs 17.5s per sample).

Gemini 3.6 FlashGrok 4.6

Gemini 3.6 Flash vs Grok 4.6 Comparison Table

Evals updated September 29, 2026Pricing updated September 29, 2026

PropertyGemini 3.6 FlashGrok 4.6
OrganizationGoogleSpaceXAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJul 2026Aug 2026
Context Window1.0M500K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.750$2.00
Output $/1M$3.75$6.00
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemoDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Video Classification
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
83.3%
68.7%
Avg cost / sample$0.0032$0.0097
Avg speed / sample14.66s17.55s
By task
Object Detection (low)
58.9%
±1.3, Mean of 3 runs, range 57.9 to 60.4
$0.0041
23.8%
±2.8, Mean of 3 runs, range 20.2 to 25.9
$0.013
Object Detection (high)
70.7%
±0.4, Mean of 3 runs, range 70.3 to 71.2
$0.0093
24.0%
±1.0, Mean of 3 runs, range 23.1 to 25.1
$0.041
Counting (low)
80.2%
±2.0, Mean of 3 runs, range 78.4 to 82.4
$0.0034
65.8%
±4.1, Mean of 3 runs, range 62.2 to 70.3
$0.0079
Counting (high)
79.3%
±2.7, Mean of 3 runs, range 77.0 to 82.4
$0.0089
56.8%
±1.4, Mean of 3 runs, range 55.4 to 58.1
$0.027
Identification (low)
99.0%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.0015
84.4%
±3.1, Mean of 3 runs, range 81.3 to 87.5
$0.0055
Identification (high)
100.0%
±0.0, Mean of 3 runs, range 100.0 to 100.0
$0.0033
85.4%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.015
OCR (low)
88.2%
±0.3, Mean of 3 runs, range 87.9 to 88.4
$0.0028
91.8%
±0.3, Mean of 3 runs, range 91.5 to 92.1
$0.0091
OCR (high)
89.5%
±0.0, Mean of 3 runs, range 89.5 to 89.6
$0.017
91.6%
±0.2, Mean of 3 runs, range 91.4 to 91.7
$0.023
Data Extraction (low)
95.9%
±1.0, Mean of 3 runs, range 94.8 to 96.9
$0.0015
85.6%
±1.0, Mean of 3 runs, range 84.5 to 86.6
$0.0050
Data Extraction (high)
94.8%
±1.0, Mean of 3 runs, range 93.8 to 95.9
$0.0032
85.6%
±1.0, Mean of 3 runs, range 84.5 to 86.6
$0.0090
Reasoning (low)
77.7%
±2.0, Mean of 3 runs, range 76.2 to 80.1
$0.0031
61.1%
±1.3, Mean of 3 runs, range 59.6 to 62.3
$0.0093
Reasoning (high)
81.0%
±2.0, Mean of 3 runs, range 79.5 to 83.4
$0.0091
63.8%
±2.0, Mean of 3 runs, range 62.3 to 66.2
$0.032

Gemini 3.6 Flash vs Grok 4.6: Overview

Gemini 3.6 Flash

Gemini 3.6 Flash is a multimodal language model from Google DeepMind, positioned as the workhorse tier in the Gemini 3.x family. It accepts text, image, video, audio, and PDF inputs with a 1 million token context window and produces up to 64,000 output tokens. The model builds directly on Gemini 3.5 Flash, incorporating developer and customer feedback to improve token efficiency, coding quality, and knowledge work performance. According to the Artificial Analysis Index, it consumes 17% fewer output tokens than its predecessor, and on some benchmarks such as DeepSWE, token reduction reaches up to 65%. It supports function calling, structured output, search as a tool, and code execution, and includes computer use as a built-in capability in the Gemini API and Gemini Enterprise.

On coding benchmarks, Gemini 3.6 Flash scores 49% on DeepSWE versus 37% for 3.5 Flash, and 63.9% on MLE Bench versus 49.7%. Computer use performance on OSWorld-Verified improves from 78.4% to 83%, and knowledge work scores on GDPval-AA v2 rise from 1349 to 1421. The model carries a knowledge cutoff of March 2026 and ships with enhanced Frontier Safety safeguards covering chemical, biological, radiological, nuclear, and cyber offense domains, with training to minimize refusals for beneficial uses. It is a proprietary, closed-weights model available in preview through the Gemini API via Google AI Studio, Android Studio, Google Antigravity, Gemini Enterprise, and the Gemini app.

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.

Frequently Asked Questions

On Roboflow's Vision Evals, Gemini 3.6 Flash performed better. It scores higher on 5 of the six vision tasks and averages 83.3% (#10 of 61) against 68.7% (#33 of 61) for Grok 4.6. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

Yes. On the Vision Evals Object Detection benchmark at low effort, Gemini 3.6 Flash leads with 58.9% against 23.8%. This is the widest gap between the two models across the benchmark's tasks.

Gemini 3.6 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0032 per sample against $0.0097. Gemini 3.6 Flash is priced at $0.75 per 1M input tokens and $3.75 per 1M output; Grok 4.6 is priced at $2.00 per 1M input tokens and $6.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Gemini 3.6 Flash is faster. Across Roboflow's Vision Evals it averaged 14.7s per inference against 17.5s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.

Yes. The comparison demo on this page runs both models on the same image side by side for open prompts and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.