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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.

Compare Claude Opus 5.5 vs Muse Spark 1.3 live

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

These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.

Models in this comparison

Claude Opus 5.5 vs Muse Spark 1.3 on Vision Evals

Claude Opus 5.5 scores higher on 5 of the six Vision Evals tasks.

The widest gap is Object Detection, where Claude Opus 5.5 leads 74.4% to 58.6%.

Overall, Claude Opus 5.5 averages 85.5% (#3 of 57) against 79.8% (#13 of 57) for Muse Spark 1.3.

Muse Spark 1.3 is cheaper ($0.0075 vs $0.014 per sample), while Claude Opus 5.5 is faster (12.8s vs 23.1s per sample).

Claude Opus 5.5Muse Spark 1.3

Claude Opus 5.5 vs Muse Spark 1.3 Comparison Table

Evals updated September 22, 2026Pricing updated September 22, 2026

PropertyClaude Opus 5.5Muse Spark 1.3
OrganizationAnthropicMeta
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateSep 2026Sep 2026
Context Window1.0M1.0M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$1.25
Output $/1M$4.25
Vision Tasks
CaptioningDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemo
OCRDemo
Vision Language
Visual Question AnsweringDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
85.5%
79.8%
Avg cost / sample$0.014$0.0075
Avg speed / sample12.76s23.14s
By task
Object Detection (low)
74.4%
±0.5, Mean of 3 runs, range 73.9 to 74.8
$0.022
58.6%
±0.7, Mean of 3 runs, range 58.0 to 59.4
$0.011
Object Detection (high)
76.8%
±1.2, Mean of 3 runs, range 75.4 to 77.8
$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)
87.8%
±0.6, Mean of 3 runs, range 87.0 to 88.2
$0.017
91.3%
±0.5, Mean of 3 runs, range 90.7 to 91.6
$0.0083
OCR (high)
87.2%
±0.6, Mean of 3 runs, range 86.5 to 87.8
$0.024
86.9%
±4.1, Mean of 3 runs, range 82.2 to 90.4
$0.015
Data Extraction (low)
93.5%
±0.5, Mean of 3 runs, range 92.8 to 93.8
$0.0066
88.7%
±1.5, Mean of 3 runs, range 86.6 to 89.7
$0.0031
Data Extraction (high)
93.5%
±0.5, Mean of 3 runs, range 92.8 to 93.8
$0.0075
87.6%
±0.0, Mean of 3 runs, range 87.6 to 87.6
$0.0044
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 5 of the six vision tasks and averages 85.5% (#3 of 57) against 79.8% (#13 of 57) 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 74.4% 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 $0.0075 per sample against $0.014. Actual costs depend on your image sizes, prompts, and output length.

Claude Opus 5.5 is faster. Across Roboflow's Vision Evals it averaged 12.8s per inference against 23.1s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.