Roboflow

Claude Fable 5.1 vs Muse Spark Open

Claude Fable 5.1 and Muse Spark Open score 74.7% vs 69.4% averaged across five Vision Evals tasks (#15 and #25 of 65 models), so Claude Fable 5.1 leads overall.

  • Claude Fable 5.1 wins 4 of the 5 tasks, with its widest lead on reasoning (72.0% vs 63.8%).
  • Muse Spark Open is about 1/7 of the cost: $0.0059 vs $0.039 overall average cost per sample.
  • Muse Spark Open is faster: 7.4s vs 8.3s per sample.

Compare Claude Fable 5.1 vs Muse Spark Open 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.

Claude Fable 5.1 vs Muse Spark Open on Vision Evals

Score by taskClaude Fable 5.1Muse Spark Open
Identification
97.9
82.3
Reasoning
72.0
63.8
Counting
69.4
75.7
OCR
72.9
67.6
Object Detection
61.4
57.8

Roboflow Vision Evals. Full breakdown below.

Claude Fable 5.1 vs Muse Spark Open Comparison Table

Evals updated October 26, 2026Pricing updated October 27, 2026

PropertyClaude Fable 5.1Muse Spark Open
OrganizationAnthropicMeta
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateSep 2026Oct 2026
Context Window1.0M1.0M
ParametersUnknown816B total / 42B active
LicenseProprietaryCustom
Commercial usecommercial use per vendor termsSee license terms
Pricing per 1M tokens
Input $/1M$10.00$1.25
Output $/1M$50.00$4.25
Vision Tasks
CaptioningDemoSupported
ClassificationDemoSupported
Object DetectionDemoSupported
OCRDemoSupported
Visual Question AnsweringDemoSupported
Both support 5 more tasks
Model Features
Both support 3 more features
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
74.7%
69.4%
Avg cost / sample$0.039$0.0059
Avg speed / sample8.35s7.37s
By task
Object Detection (low)
61.4%
±0.5, Mean of 3 runs, range 61.0 to 62.0
$0.060
57.8%
±0.6, Mean of 3 runs, range 57.0 to 58.2
$0.0073
Object Detection (high)
65.0%
±0.4, Mean of 3 runs, range 64.6 to 65.3
$0.078
60.9%
±0.8, Mean of 3 runs, range 60.3 to 61.9
$0.013
Counting (low)
69.4%
±2.7, Mean of 3 runs, range 66.2 to 71.6
$0.019
75.7%
±2.7, Mean of 3 runs, range 73.0 to 78.4
$0.0036
Counting (high)
73.0%
±4.7, Mean of 3 runs, range 67.6 to 77.0
$0.023
75.2%
±4.1, Mean of 3 runs, range 71.6 to 79.7
$0.0073
Identification (low)
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.013
82.3%
±1.6, Mean of 3 runs, range 81.3 to 84.4
$0.0027
Identification (high)
96.9%
±3.1, Mean of 3 runs, range 93.8 to 100.0
$0.014
80.2%
±3.1, Mean of 3 runs, range 78.1 to 84.4
$0.0056
OCR (low)
72.9%
$0.039
67.6%
$0.0061
by category
Single value
64.3%
Transcription
84.7%
Structured JSON
89.2%
Text localization
46.5%
Single value
60.0%
Transcription
89.0%
Structured JSON
85.5%
Text localization
29.5%
OCR (high)
75.3%
$0.051
68.6%
$0.014
by category
Single value
69.1%
Transcription
95.2%
Structured JSON
89.5%
Text localization
43.4%
Single value
58.3%
Transcription
91.4%
Structured JSON
88.2%
Text localization
32.2%
Reasoning (low)
72.0%
±1.3, Mean of 3 runs, range 70.9 to 73.5
$0.019
63.8%
±1.0, Mean of 3 runs, range 62.9 to 64.9
$0.0049
Reasoning (high)
73.1%
±2.0, Mean of 3 runs, range 71.5 to 75.5
$0.028
65.1%
±3.0, Mean of 3 runs, range 62.3 to 68.2
$0.012

Claude Fable 5.1 vs Muse Spark Open: Overview

Claude Fable 5.1

Claude Fable 5.1 is a proprietary multimodal model from Anthropic in the Mythos-class tier of the Claude 5 family, positioned above Claude Opus for demanding reasoning and long-horizon agentic work. It accepts text and images as input and returns text, with a one million token context window and a maximum output of 128 thousand tokens. Adaptive thinking is always on, and an effort parameter controls how much reasoning the model applies to a given request. Anthropic reports a reliable knowledge and training data cutoff of June 2026. Claude Fable 5.1 and Claude Mythos 5.1 share the same underlying model; the difference between them is the set of safety classifiers applied to dual-use cybersecurity and biology requests.

On the vision side, Anthropic documents improvements in reading dense charts, financial filings, and tables nested inside PDF documents, which extends the model toward document understanding, chart question answering, and spreadsheet and slide work. Model weights are not published.

Muse Spark Open

Muse Spark Open is an open-weight multimodal model released by Meta on October 15, 2026. Its sparse mixture-of-experts architecture has 816 billion total parameters and activates 42 billion per token. It accepts text, images, audio and video, produces text, and supports a context window of 1,048,576 tokens. Meta provides BF16 and NVFP4 checkpoints for self-hosting, alongside access through hosted inference partners.

The model is designed for coding, tool use and multi-step reasoning over long tasks. Its visual inputs support workflows involving screenshots, documents and other image content. Vision Evals measures its text understanding, counting, identification, reasoning and object detection at Low and High effort. The published weights use the custom Muse Model License, with commercial use subject to its terms and the accompanying usage policy.

Frequently Asked Questions

On Roboflow's Vision Evals, Claude Fable 5.1 performed better. It scores higher on 4 of the five vision tasks and averages 74.7% (#15 of 65) against 69.4% (#25 of 65) for Muse Spark Open. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

Yes. On the Vision Evals Identification benchmark at low effort, Claude Fable 5.1 leads with 97.9% against 82.3%. This is the widest gap between the two models across the benchmark's tasks.

Muse Spark Open is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0059 per sample against $0.039. Claude Fable 5.1 is priced at $10.00 per 1M input tokens and $50.00 per 1M output; Muse Spark Open 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.

Muse Spark Open is faster. Across Roboflow's Vision Evals it averaged 7.4s per inference against 8.3s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.