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Claude Opus 5.5 vs Muse Spark 1.3

Compare Claude Opus 5.5 and Muse Spark 1.3 side-by-side. See how these vision models stack up in Image Captioning, OCR, Classification, Object Detection, and Open Prompt.

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AnthropicClaude Opus 5.5
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MetaMuse Spark 1.3
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Models in this comparison

Claude Opus 5.5 vs Muse Spark 1.3 on Vision Evals

Claude Opus 5.5 scores higher on all five Vision Evals tasks.

The widest gap is Object Detection, where Claude Opus 5.5 leads 74.5% to 58.6%.

Overall, Claude Opus 5.5 averages 82.0% (#3 of 63) against 73.9% (#16 of 63) for Muse Spark 1.3.

Muse Spark 1.3 is cheaper ($0.0084 vs $0.015 per sample), while Claude Opus 5.5 is faster (7.6s vs 25.5s per sample).

Claude Opus 5.5Muse Spark 1.3

Claude Opus 5.5 vs Muse Spark 1.3 Comparison Table

Evals updated October 13, 2026Pricing updated October 17, 2026

PropertyClaude Opus 5.5Muse Spark 1.3
OrganizationAnthropicMeta
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateSep 2026Sep 2026
Context Window1.0M1.0M
ParametersUnknownUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$4.00$1.25
Output $/1M$20.00$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
82.0%
73.9%
Avg cost / sample$0.015$0.0084
Avg speed / sample7.63s25.50s
By task
Object Detection (low)
74.5%
±0.5, Mean of 3 runs, range 74.0 to 75.0
$0.021
58.6%
±0.7, Mean of 3 runs, range 58.0 to 59.4
$0.011
Object Detection (high)
76.0%
±1.1, Mean of 3 runs, range 74.7 to 77.0
$0.030
56.6%
±2.4, Mean of 3 runs, range 54.5 to 59.3
$0.017
Counting (low)
80.6%
±2.0, Mean of 3 runs, range 78.4 to 82.4
$0.0081
74.3%
±2.0, Mean of 3 runs, range 73.0 to 77.0
$0.0049
Counting (high)
82.0%
±2.0, Mean of 3 runs, range 79.7 to 83.8
$0.0098
75.7%
±3.4, Mean of 3 runs, range 73.0 to 79.7
$0.0094
Identification (low)
93.8%
±0.0, Mean of 3 runs, range 93.8 to 93.8
$0.0058
92.7%
±1.6, Mean of 3 runs, range 90.6 to 93.8
$0.0036
Identification (high)
95.8%
±1.6, Mean of 3 runs, range 93.8 to 96.9
$0.0067
86.5%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.0063
OCR (low)
78.3%
$0.016
70.4%
$0.0086
by category
Single value
67.8%
Transcription
96.7%
Structured JSON
91.5%
Text localization
61.0%
Single value
62.6%
Transcription
91.8%
Structured JSON
88.0%
Text localization
33.3%
OCR (high)
79.9%
$0.023
69.8%
$0.015
by category
Single value
69.6%
Transcription
96.1%
Structured JSON
94.1%
Text localization
61.1%
Single value
62.2%
Transcription
86.8%
Structured JSON
87.2%
Text localization
35.2%
Reasoning (low)
83.0%
±1.0, Mean of 3 runs, range 82.1 to 84.1
$0.0090
73.3%
±1.0, Mean of 3 runs, range 72.2 to 74.2
$0.0064
Reasoning (high)
85.9%
±2.6, Mean of 3 runs, range 82.8 to 88.1
$0.011
73.1%
±1.0, Mean of 3 runs, range 72.2 to 74.2
$0.012

Claude Opus 5.5 vs Muse Spark 1.3: Overview

Claude Opus 5.5

Claude Opus 5.5 is a proprietary multimodal reasoning model from Anthropic and the first entry in the Claude 5.5 family. It accepts interleaved text and image input and returns text, with a one million token context window and up to 128,000 output tokens per response. Adaptive thinking is always enabled on this model and cannot be disabled; thinking depth is instead governed by an effort parameter with five levels, where medium is the default, a change from the high default used by Claude Opus 5 and earlier Opus models. Anthropic reports a knowledge cutoff of June 2026.

On the visual side, Anthropic characterizes Opus 5.5 as its strongest Opus release for vision and computer use, describing improved reading of dense documents, charts, screenshots, and diagrams for document extraction and visual analysis tasks. Published results include 89.0% on Chartography with tools and 81.8% on OSWorld 2.0 under partial credit scoring, alongside 48.7% under strict scoring reported in the system card. The accompanying system card states that Opus 5.5 scored higher than Opus 5 on every evaluation in its capability summary, with the largest gains concentrated in agentic coding, visual reasoning, computer use, and long-horizon knowledge work. The model ships with safety classifiers covering biology and cybersecurity that can route blocked requests to earlier Claude models.

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.

Frequently Asked Questions

On Roboflow's Vision Evals, Claude Opus 5.5 performed better. It scores higher on all five vision tasks and averages 82.0% (#3 of 63) against 73.9% (#16 of 63) for Muse Spark 1.3. 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, Claude Opus 5.5 leads with 74.5% against 58.6%. This is the widest gap between the two models across the benchmark's tasks.

Muse Spark 1.3 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0084 per sample against $0.015. Claude Opus 5.5 is priced at $4.00 per 1M input tokens and $20.00 per 1M output; Muse Spark 1.3 is priced at $1.25 per 1M input tokens and $4.25 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Claude Opus 5.5 is faster. Across Roboflow's Vision Evals it averaged 7.6s per inference against 25.5s. 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 image captioning and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.