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Claude Opus 5.5 vs Muse Spark 1.1

Compare Claude Opus 5.5 and Muse Spark 1.1 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 1.1
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Models in this comparison

Claude Opus 5.5 vs Muse Spark 1.1 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 60.6%.

Overall, Claude Opus 5.5 averages 82.0% (#3 of 63) against 74.4% (#15 of 63) for Muse Spark 1.1.

Muse Spark 1.1 is both cheaper ($0.0075 vs $0.015 per sample) and faster (7.2s vs 7.6s per sample).

Claude Opus 5.5Muse Spark 1.1

Claude Opus 5.5 vs Muse Spark 1.1 Comparison Table

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

PropertyClaude Opus 5.5Muse Spark 1.1
OrganizationAnthropicMeta
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateSep 2026Jul 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%
74.4%
Avg cost / sample$0.015$0.0075
Avg speed / sample7.63s7.15s
By task
Object Detection (low)
74.5%
±0.5, Mean of 3 runs, range 74.0 to 75.0
$0.021
60.6%
±1.9, Mean of 3 runs, range 58.4 to 62.1
$0.0097
Object Detection (high)
76.0%
±1.1, Mean of 3 runs, range 74.7 to 77.0
$0.030
60.0%
±0.5, Mean of 3 runs, range 59.6 to 60.7
$0.015
Counting (low)
80.6%
±2.0, Mean of 3 runs, range 78.4 to 82.4
$0.0081
76.6%
±1.3, Mean of 3 runs, range 75.7 to 78.4
$0.0042
Counting (high)
82.0%
±2.0, Mean of 3 runs, range 79.7 to 83.8
$0.0098
76.1%
±0.7, Mean of 3 runs, range 75.7 to 77.0
$0.0079
Identification (low)
93.8%
±0.0, Mean of 3 runs, range 93.8 to 93.8
$0.0058
91.7%
±1.6, Mean of 3 runs, range 90.6 to 93.8
$0.0033
Identification (high)
95.8%
±1.6, Mean of 3 runs, range 93.8 to 96.9
$0.0067
89.6%
±1.6, Mean of 3 runs, range 87.5 to 90.6
$0.0065
OCR (low)
78.3%
$0.016
68.8%
$0.0076
by category
Single value
67.8%
Transcription
96.7%
Structured JSON
91.5%
Text localization
61.0%
Single value
60.4%
Transcription
90.1%
Structured JSON
86.1%
Text localization
33.9%
OCR (high)
79.9%
$0.023
67.5%
$0.015
by category
Single value
69.6%
Transcription
96.1%
Structured JSON
94.1%
Text localization
61.1%
Single value
60.4%
Transcription
81.6%
Structured JSON
85.7%
Text localization
31.4%
Reasoning (low)
83.0%
±1.0, Mean of 3 runs, range 82.1 to 84.1
$0.0090
74.2%
±1.7, Mean of 3 runs, range 72.2 to 75.5
$0.0061
Reasoning (high)
85.9%
±2.6, Mean of 3 runs, range 82.8 to 88.1
$0.011
76.6%
±1.3, Mean of 3 runs, range 75.5 to 78.2
$0.013

Claude Opus 5.5 vs Muse Spark 1.1: 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 1.1

Muse Spark 1.1 is a natively multimodal reasoning model from Meta Superintelligence Labs, released on July 9, 2026, as a significant upgrade to the original Muse Spark. The model accepts text, image, video, PDF, and audio as input and produces text output. It operates with a 1-million-token context window (1,048,576 tokens per the Meta Model API documentation) and is designed specifically for agentic tasks that require planning, tool use, computer use, and multi-agent orchestration. The model runs in a "Thinking" mode, where adjustable reasoning effort is applied before generating a response. It can function both as a main agent gathering context, forming plans, and delegating to parallel subagents and as a subagent that adheres to assigned tasks and escalates when needed. It is trained to decide autonomously when to write automation scripts versus interact directly with a user interface.

Muse Spark 1.1 supports a range of multimodal capabilities including visual perception, image and video captioning, visual-to-code generation, and document analysis. The model was evaluated under Meta's Advanced AI Scaling Framework across frontier risk categories including chemical and biological threats, cybersecurity, and loss-of-control scenarios. Parameter count, architecture details, and training data composition are not publicly disclosed. The model is proprietary and closed-weight, accessible to consumers through the Meta AI app and to developers via the Meta Model API, which launched in public preview alongside this release.