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Grok 4.6 vs Muse Spark 1.3

Compare Grok 4.6 and Muse Spark 1.3 side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, Classification, OCR, and Object Detection.

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GrokGrok 4.6
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MetaMuse Spark 1.3
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Models in this comparison

Grok 4.6 vs Muse Spark 1.3 on Vision Evals

Muse Spark 1.3 scores higher on all five Vision Evals tasks.

The widest gap is Object Detection, where Muse Spark 1.3 leads 58.6% to 23.8%.

Overall, Grok 4.6 averages 59.1% (#36 of 63) against 73.9% (#16 of 63) for Muse Spark 1.3.

Muse Spark 1.3 is cheaper ($0.0084 vs $0.011 per sample), while Grok 4.6 is faster (19.3s vs 25.5s per sample).

Grok 4.6Muse Spark 1.3

Grok 4.6 vs Muse Spark 1.3 Comparison Table

Evals updated October 13, 2026Pricing updated October 16, 2026

PropertyGrok 4.6Muse Spark 1.3
OrganizationSpaceXAIMeta
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateAug 2026Sep 2026
Context Window500K1.0M
ParametersUnknownUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$2.00$1.25
Output $/1M$6.00$4.25
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 5 vision tasks, pooled at low effort
Overall
59.1%
73.9%
Avg cost / sample$0.011$0.0084
Avg speed / sample19.32s25.50s
By task
Object Detection (low)
23.8%
±2.8, Mean of 3 runs, range 20.2 to 25.9
$0.013
58.6%
±0.7, Mean of 3 runs, range 58.0 to 59.4
$0.011
Object Detection (high)
24.0%
±1.0, Mean of 3 runs, range 23.1 to 25.1
$0.041
56.6%
±2.4, Mean of 3 runs, range 54.5 to 59.3
$0.017
Counting (low)
65.8%
±4.1, Mean of 3 runs, range 62.2 to 70.3
$0.0079
74.3%
±2.0, Mean of 3 runs, range 73.0 to 77.0
$0.0049
Counting (high)
56.8%
±1.4, Mean of 3 runs, range 55.4 to 58.1
$0.027
75.7%
±3.4, Mean of 3 runs, range 73.0 to 79.7
$0.0094
Identification (low)
84.4%
±3.1, Mean of 3 runs, range 81.3 to 87.5
$0.0055
92.7%
±1.6, Mean of 3 runs, range 90.6 to 93.8
$0.0036
Identification (high)
85.4%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.015
86.5%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.0063
OCR (low)
60.6%
$0.011
70.4%
$0.0086
by category
Single value
50.0%
Transcription
89.0%
Structured JSON
84.4%
Text localization
11.0%
Single value
62.6%
Transcription
91.8%
Structured JSON
88.0%
Text localization
33.3%
OCR (high)
61.2%
$0.030
69.8%
$0.015
by category
Single value
50.9%
Transcription
88.7%
Structured JSON
85.7%
Text localization
9.4%
Single value
62.2%
Transcription
86.8%
Structured JSON
87.2%
Text localization
35.2%
Reasoning (low)
61.1%
±1.3, Mean of 3 runs, range 59.6 to 62.3
$0.0093
73.3%
±1.0, Mean of 3 runs, range 72.2 to 74.2
$0.0064
Reasoning (high)
63.8%
±2.0, Mean of 3 runs, range 62.3 to 66.2
$0.032
73.1%
±1.0, Mean of 3 runs, range 72.2 to 74.2
$0.012

Grok 4.6 vs Muse Spark 1.3: 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. Independent measurement from Artificial Analysis places the model at 61 on its Intelligence Index, five points above Grok 4.5.

Muse Spark 1.3

Muse Spark 1.3 is a proprietary multimodal reasoning model from Meta Superintelligence Labs and the fourth Muse Spark release in five months, arriving on September 2, 2026. It takes text, images, video, and document files as input and returns text, and it operates over a context window of 1,048,576 tokens. Meta trains the model for long-horizon agentic work, so it carries accumulated context and prior tool results forward across many turns, reconciles messy or conflicting inputs, and asks for clarification when a task is underspecified. Visual inputs such as screenshots and video clips feed a reasoning loop that runs against a real execution environment rather than a scripted sequence of steps.

The model exposes graded reasoning effort settings. An xhigh configuration is generally available at launch, while a max reasoning configuration aimed at harder reasoning and agentic problems arrives after further safety testing. Artificial Analysis measures Muse Spark 1.3 (max) at 62 on its Intelligence Index and the xhigh configuration at 61, with agentic tool-use evaluations driving most of the gain over Muse Spark 1.2; max reaches 52% on Tau3-Bench Banking by spending more turns and reasoning tokens than xhigh. Prior Muse Spark versions emit bounding box coordinates, transcriptions, and structured field extractions from images on Roboflow Vision Evals.