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Muse Spark 1.3 vs SAM 3

Compare Muse Spark 1.3 and SAM 3 side-by-side. See how these vision models stack up in Object Detection.

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MetaMuse Spark 1.3
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MetaSAM 3
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Models in this comparison

Meta

Muse Spark 1.3 vs SAM 3 Comparison Table

Evals updated October 13, 2026Pricing updated October 18, 2026

PropertyMuse Spark 1.3SAM 3
OrganizationMetaMeta
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateSep 2026Nov 2025
Context Window1.0M—
ParametersUnknownUnknown
LicenseProprietaryCustom
Commercial usecommercial use per vendor termsSee license terms
Pricing per 1M tokens
Input $/1M$1.25No published price
Output $/1M$4.25No published price
Vision Tasks
Object DetectionDemoDemo
CaptioningDemoNot listed
Chart Question AnsweringSupportedNot listed
ClassificationDemoNot listed
Document Question AnsweringSupportedNot listed
Image TaggingSupportedNot listed
Instance SegmentationNot listedSupported
Multi-Label ClassificationSupportedNot listed
OCRDemoNot listed
Open Vocabulary Object DetectionNot listedSupported
Promptable Concept SegmentationNot listedDemo
Video Object TrackingNot listedSupported
Vision LanguageSupportedNot listed
Visual Question AnsweringDemoNot listed
Zero Shot SegmentationNot listedSupported
Model Features
Foundation VisionSupportedSupported
Multimodal VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedNot listed
Zero-shot DetectionNot listedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
73.9%
Not evaluated
Avg cost / sample$0.0084–
Avg speed / sample25.50s–
By task
Object Detection (low)
58.6%
±0.7, Mean of 3 runs, range 58.0 to 59.4
$0.011
–
Object Detection (high)
56.6%
±2.4, Mean of 3 runs, range 54.5 to 59.3
$0.017
–
Counting (low)
74.3%
±2.0, Mean of 3 runs, range 73.0 to 77.0
$0.0049
–
Counting (high)
75.7%
±3.4, Mean of 3 runs, range 73.0 to 79.7
$0.0094
–
Identification (low)
92.7%
±1.6, Mean of 3 runs, range 90.6 to 93.8
$0.0036
–
Identification (high)
86.5%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.0063
–
OCR (low)
70.4%
$0.0086
–
by category
Single value
62.6%
Transcription
91.8%
Structured JSON
88.0%
Text localization
33.3%
OCR (high)
69.8%
$0.015
–
by category
Single value
62.2%
Transcription
86.8%
Structured JSON
87.2%
Text localization
35.2%
Reasoning (low)
73.3%
±1.0, Mean of 3 runs, range 72.2 to 74.2
$0.0064
–
Reasoning (high)
73.1%
±1.0, Mean of 3 runs, range 72.2 to 74.2
$0.012
–

Muse Spark 1.3 vs SAM 3: Overview

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.

SAM 3

Released on November 19th, 2025, Segment Anything 3 (SAM 3) is a zero-shot image segmentation model that “detects, segments, and tracks objects in images and videos based on concept prompts.” This model was developed by Meta as the third model in the Segment Anything series.

Unlike its previous SAM models (Segment Anything and Segment Anything 2), you can provide SAM 3 with the prompt “shipping container” and it will generate precise segmentation masks for all shipping containers in an image. SAM 3 generates segmentation masks that correspond to the location of the objects found with a text prompt.

Frequently Asked Questions

SAM 3 has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.

Muse Spark 1.3 is released under Proprietary, while SAM 3 uses Custom. In practice: Muse Spark 1.3 — 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.

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