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GPT-5.5 vs Grok 4.6

Compare GPT-5.5 and Grok 4.6 side-by-side. See how these vision models stack up in Object Detection, Image Captioning, Classification, Open Prompt, and OCR.

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Run the same image across every model that supports a task and compare their outputs side-by-side.

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OpenAIGPT-5.5
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GrokGrok 4.6
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Models in this comparison

OpenAI

GPT-5.5 vs Grok 4.6 on Vision Evals

GPT-5.5 scores higher on 5 of the six Vision Evals tasks.

The widest gap is Object Detection, where GPT-5.5 leads 43.6% to 23.8%.

Overall, GPT-5.5 averages 74.8% (#21 of 60) against 68.7% (#33 of 60) for Grok 4.6.

Grok 4.6 is cheaper ($0.0097 vs $0.022 per sample), while GPT-5.5 is faster (9.0s vs 17.5s per sample).

GPT-5.5Grok 4.6

GPT-5.5 vs Grok 4.6 Comparison Table

Evals updated October 7, 2026Pricing updated October 7, 2026

PropertyGPT-5.5Grok 4.6
OrganizationOpenAISpaceXAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateApr 2026Aug 2026
Context Window1.0M500K
ParametersUnknownUnknown
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$5.00$2.00
Output $/1M$30.00$6.00
Vision Tasks
CaptioningDemoDemo
Chart Question AnsweringSupportedSupported
ClassificationDemoDemo
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionDemoDemo
OCRDemoDemo
Vision LanguageSupportedSupported
Visual Question AnsweringDemoDemo
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
74.8%
68.7%
Avg cost / sample$0.022$0.0097
Avg speed / sample9.03s17.55s
By task
Object Detection (low)
43.6%
±2.2, Mean of 3 runs, range 41.7 to 46.1
$0.034
23.8%
±2.8, Mean of 3 runs, range 20.2 to 25.9
$0.013
Object Detection (high)
44.2%
±0.6, Mean of 3 runs, range 43.5 to 44.8
$0.130
24.0%
±1.0, Mean of 3 runs, range 23.1 to 25.1
$0.041
Counting (low)
68.0%
±3.4, Mean of 3 runs, range 64.9 to 71.6
$0.015
65.8%
±4.1, Mean of 3 runs, range 62.2 to 70.3
$0.0079
Counting (high)
68.0%
±1.4, Mean of 3 runs, range 66.2 to 68.9
$0.049
56.8%
±1.4, Mean of 3 runs, range 55.4 to 58.1
$0.027
Identification (low)
89.6%
±1.6, Mean of 3 runs, range 87.5 to 90.6
$0.0087
84.4%
±3.1, Mean of 3 runs, range 81.3 to 87.5
$0.0055
Identification (high)
88.5%
±1.6, Mean of 3 runs, range 87.5 to 90.6
$0.018
85.4%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.015
OCR (low)
91.2%
±0.3, Mean of 3 runs, range 90.9 to 91.6
$0.024
91.8%
±0.3, Mean of 3 runs, range 91.5 to 92.1
$0.0091
OCR (high)
91.7%
±0.6, Mean of 3 runs, range 91.1 to 92.3
$0.072
91.6%
±0.2, Mean of 3 runs, range 91.4 to 91.7
$0.023
Data Extraction (low)
85.9%
±1.5, Mean of 3 runs, range 84.5 to 87.6
$0.011
85.6%
±1.0, Mean of 3 runs, range 84.5 to 86.6
$0.0050
Data Extraction (high)
86.9%
±0.5, Mean of 3 runs, range 86.6 to 87.6
$0.019
85.6%
±1.0, Mean of 3 runs, range 84.5 to 86.6
$0.0090
Reasoning (low)
70.6%
±1.0, Mean of 3 runs, range 69.5 to 71.5
$0.015
61.1%
±1.3, Mean of 3 runs, range 59.6 to 62.3
$0.0093
Reasoning (high)
72.2%
±3.6, Mean of 3 runs, range 68.9 to 76.2
$0.044
63.8%
±2.0, Mean of 3 runs, range 62.3 to 66.2
$0.032

GPT-5.5 vs Grok 4.6: Overview

GPT-5.5

GPT-5.5 is a multimodal large language model released by OpenAI on April 23, 2026, engineered for autonomous, multi-step knowledge work and agentic workflows. It accepts text, images, and code as input, featuring enhanced spatial reasoning and visual grounding to support its computer use capabilities for operating software and navigating UI elements. Built to execute complex workflows end-to-end, the model interprets loosely defined tasks, selects appropriate tools, and performs self-verification with minimal user intervention. It is available in a standard version, a Thinking mode for extended reasoning budgets, and a Pro variant that uses parallel test-time compute for maximum precision on complex tasks.

Co-optimized with NVIDIA for GB200 NVL72 infrastructure, GPT-5.5 delivers per-token latency comparable to its predecessor GPT-5.4 while maintaining a 1-million-token context window. Despite increased capability, the model achieves greater token efficiency in coding and data analysis workflows, often completing tasks with fewer total tokens than previous versions. OpenAI reports a 60% reduction in hallucination rate compared to GPT-5.4, improving reliability for accuracy-sensitive applications. API access is available via the Responses and Chat Completions endpoints.

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.