Fronset Benchmark

Meta Muse Spark 1.1 (archived)

Provider
OpenRouter
Model name
meta/muse-spark-1.1
Last benchmarked
Qualified on
29 / 52 tasks (at the 90% bar)
Best value on
1 tasks

Good enough on 29/52 tasks at the 90% bar. Best value on 1 task. Best fit for: Structured Data & Fact Extraction, Financial Analysis & Trading Decisions, Relevance, Classification & Matching, Social & Promotional Content, Topic Organization & Clustering.

Cost vs quality across all tasks, as of 5 September 2026

0%25%50%75%100%78910Quality score (7–10)Cost-efficiency vs best value (1.0 = best value)Thematic Topic Discovery — quality 8.28, 14.3x the cost of the best-value good-enough optionAuthoritative Source Selection — quality 8.00, 19.9x the cost of the best-value good-enough optionBatch Text Translation — quality 8.85, 15.5x the cost of the best-value good-enough optionTopic Cluster Labeling — quality 8.39, 8.0x the cost of the best-value good-enough optionTopic Sequence Optimization — quality 8.74, 36.9x the cost of the best-value good-enough optionResearch Region Identification — quality 8.30, 4.0x the cost of the best-value good-enough optionProfiled Document Analysis — quality 8.41, 4.7x the cost of the best-value good-enough optionTopic Section Assignment — quality 8.05, 45.4x the cost of the best-value good-enough optionPublication Title Package Generation — quality 8.62, 12.4x the cost of the best-value good-enough optionReport Outline Generation — quality 8.92, 14.1x the cost of the best-value good-enough optionSocial Post Portfolio Selection — quality 8.38, 133.3x the cost of the best-value good-enough optionContent Set Relevance Scoring — quality 7.24, 5.6x the cost of the best-value good-enough optionProfiled Document Structure Extraction — quality 8.64, 6.3x the cost of the best-value good-enough optionShort Post Batch Relevance Scoring — quality 7.45, 33.6x the cost of the best-value good-enough optionModel Specific Prompt Adaptation — quality 8.72, 31.7x the cost of the best-value good-enough optionStructured Output Extraction — quality 9.02, 59.2x the cost of the best-value good-enough optionPersona Policy Eligibility Check — quality 9.07, 33.9x the cost of the best-value good-enough optionShort Promotional Teaser Generation — quality 8.42, 39.0x the cost of the best-value good-enough optionMulti Perspective Decision Synthesis — quality 8.50, 18.7x the cost of the best-value good-enough optionGenerated Content Relevance Scoring — quality 8.94, 15.3x the cost of the best-value good-enough optionLanguage Identification — quality 9.85, 55.5x the cost of the best-value good-enough optionReference Preserving Analytical Writing — quality 8.66, 26.4x the cost of the best-value good-enough optionProfiled Document Section Analysis — quality 9.09, 13.7x the cost of the best-value good-enough optionPublic Response Generation — quality 7.89, 13.2x the cost of the best-value good-enough optionEngagement Opportunity Triage — quality 8.76, 37.9x the cost of the best-value good-enough optionTopic Taxonomy Matching — quality 8.23, 9.1x the cost of the best-value good-enough optionPromotional Message Generation — quality 8.70, 19.4x the cost of the best-value good-enough optionContent To Image Prompt Generation — quality 8.78, 26.1x the cost of the best-value good-enough optionContent Domain Suggestion — quality 8.71, this model IS the best-value good-enough option★

within ~1.3× of the best-value model · 1.3–2× · >2× · ★ this model is the best-value pick on that task. Top-right = best quadrant. Only tasks where this model qualifies at the 90% bar are plotted.

Per-task breakdown, as of 5 September 2026

TaskCategoryQuality (% of best)ConfidenceOverpay
Content Domain Suggestion ★Relevance, Classification & Matching95%MEDIUMbest value
Research Region IdentificationStructured Data & Fact Extraction94%MEDIUM4x
Profiled Document AnalysisFinancial Analysis & Trading Decisions96%HIGH4.7x
Content Set Relevance Scoring bestRelevance, Classification & Matching100%MEDIUM5.6x
Profiled Document Structure ExtractionStructured Data & Fact Extraction91%MEDIUM6.3x
Topic Cluster LabelingTopic Organization & Clustering94%MEDIUM8x
Topic Taxonomy MatchingRelevance, Classification & Matching98%HIGH9.1x
Publication Title Package GenerationContent Summarization & Synthesis94%RANKED12x
Public Response GenerationSocial & Promotional Content93%HIGH13x
Profiled Document Section AnalysisFinancial Analysis & Trading Decisions100%RANKED14x
Report Outline GenerationLong-form Content Generation93%RANKED14x
Thematic Topic DiscoveryTopic Organization & Clustering98%HIGH14x
Generated Content Relevance ScoringRelevance, Classification & Matching97%MEDIUM15x
Batch Text TranslationInfrastructure & Utility94%HIGH16x
Multi Perspective Decision SynthesisFinancial Analysis & Trading Decisions96%HIGH19x
Promotional Message GenerationSocial & Promotional Content100%RANKED19x
Authoritative Source SelectionRelevance, Classification & Matching91%HIGH20x
Content To Image Prompt GenerationInfrastructure & Utility98%RANKED26x
Reference Preserving Analytical WritingLong-form Content Generation94%RANKED26x
Model Specific Prompt AdaptationInfrastructure & Utility99%HIGH32x
Short Post Batch Relevance ScoringRelevance, Classification & Matching98%MEDIUM34x
Persona Policy Eligibility CheckRelevance, Classification & Matching98%RANKED34x
Topic Sequence OptimizationTopic Organization & Clustering97%HIGH37x
Engagement Opportunity TriageRelevance, Classification & Matching99%HIGH38x
Short Promotional Teaser GenerationSocial & Promotional Content96%RANKED39x
Topic Section AssignmentTopic Organization & Clustering92%MEDIUM45x
Language IdentificationRelevance, Classification & Matching98%RANKED55x
Structured Output ExtractionStructured Data & Fact Extraction92%MEDIUM59x
Social Post Portfolio SelectionRelevance, Classification & Matching95%RANKED133x

Overpay — how much more you pay by running this model instead of the best-value model that clears the quality bar on that task (marked ★). "16x" means you overpay 16× — the same output for 16× the best-value good-enough option; ★ means this model is that option (no overpayment). Confidence — how sure we are about the quality score (more judgments + more agreement = higher confidence): RANKED many independent judges scored this model's outputs and their agreement is very high (most confident) — HIGH many judges have scored it and they mostly agree (well-pinned) — MEDIUM enough judges have weighed in to publish, but they disagree more than we'd like (treat with a small grain of salt). LOW-confidence cells are hidden everywhere on the site. See the methodology for the exact thresholds.