Roboflow

Grok 4.6 vs Grok 4.7

Grok 4.7 and Grok 4.6 score 63.5% vs 59.1% averaged across five Vision Evals tasks (#36 and #41 of 68 models), so Grok 4.7 leads overall.

  • Grok 4.7 wins 4 of the 5 tasks, with its widest lead on object detection (40.4% vs 23.8%).
  • Grok 4.6 is about half the cost: $0.011 vs $0.020 overall average cost per sample.
  • Grok 4.6 is faster: 19.3s vs 33.3s per sample.

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GrokGrok 4.6
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GrokGrok 4.7
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Grok 4.6 vs Grok 4.7 on Vision Evals

Score by taskGrok 4.6Grok 4.7
Object Detection
23.8
40.4
Counting
65.8
61.7
Identification
84.4
87.5
Reasoning
61.1
64.2
OCR
60.6
63.6

Roboflow Vision Evals. Full breakdown below.

Grok 4.6 vs Grok 4.7 Comparison Table

Evals updated November 10, 2026Pricing updated November 11, 2026

PropertyGrok 4.6Grok 4.7
OrganizationSpaceXAISpaceXAI
Categoryclosedclosed
Modalitymultimodal—
Release DateAug 2026Sep 2026
Context Window500K500K
ParametersUnknownUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$2.00$2.00
Output $/1M$6.00$6.00
Vision Tasks
Both support 10 more tasks
Model Features
Foundation VisionSupportedNot listed
LLMs with Vision CapabilitiesSupportedNot listed
Multimodal VisionSupportedNot listed
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
59.1%
63.5%
Avg cost / sample$0.011$0.020
Avg speed / sample19.32s33.31s
By task
Object Detection (low)
23.8%
±2.8, Mean of 3 runs, range 20.2 to 25.9
$0.013
40.4%
±0.6, Mean of 3 runs, range 39.8 to 41.0
$0.021
Object Detection (high)
24.0%
±1.0, Mean of 3 runs, range 23.1 to 25.1
$0.041
41.2%
±1.6, Mean of 3 runs, range 39.6 to 42.8
$0.028
Counting (low)
65.8%
±4.1, Mean of 3 runs, range 62.2 to 70.3
$0.0079
61.7%
±1.3, Mean of 3 runs, range 60.8 to 63.5
$0.011
Counting (high)
56.8%
±1.4, Mean of 3 runs, range 55.4 to 58.1
$0.027
60.8%
±1.3, Mean of 3 runs, range 59.5 to 62.2
$0.017
Identification (low)
84.4%
±3.1, Mean of 3 runs, range 81.3 to 87.5
$0.0055
87.5%
±3.1, Mean of 3 runs, range 84.4 to 90.6
$0.0063
Identification (high)
85.4%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.015
80.2%
±1.6, Mean of 3 runs, range 78.1 to 81.3
$0.0093
OCR (low)
60.6%
$0.011
63.6%
$0.023
by category
Single value
50.0%
Transcription
89.0%
Structured JSON
84.4%
Text localization
11.0%
Single value
54.4%
Transcription
89.5%
Structured JSON
86.4%
Text localization
14.8%
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
64.2%
±2.3, Mean of 3 runs, range 62.3 to 66.9
$0.015
Reasoning (high)
63.8%
±2.0, Mean of 3 runs, range 62.3 to 66.2
$0.032
66.9%
±1.3, Mean of 3 runs, range 65.6 to 68.2
$0.024

Grok 4.6 vs Grok 4.7: Overview

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.

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.