Muse Spark 1.1
Meta · 1 configuration
Intelligence33.7
Input / 1M$1.25
Output / 1M$4.25
Context1M
Tariff: Meta · Source: artificial-analysis · USD per million tokens
Thinking configuration
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Compare this model’s measured thinking configurations.
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Efficient frontier: best measured score at each cost1 measured configurations · 0 without both values
Selected: thinking xhigh · Click a point to switch configuration
Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, and PDF documents and returns text, with a 1M-token context window....
Intelligence IndexArtificial Analysis composite index, not a percentage. Different versions of the index are not directly comparable.
33.7 pointsDeepSWE · pass@1Software-engineering tasks on mini-swe-agent v1.1. Pass@1 across evaluated runs, with measured cost per task. The 95% intervals may overlap.
53.3 % ±3.0GPQA DiamondGraduate-level scientific questions. Measures specialist reasoning rather than web-search quality.
89.8 %Humanity’s Last ExamDifficult questions across many disciplines, compared under the same evaluation setup.
46.2 %SciCodeCode generation for scientific research problems.
58.8 %Terminal-Bench 2.1Agent tasks in a terminal environment. Results also depend on the evaluation harness.
77.9 %Omniscience accuracyFactual accuracy in Artificial Analysis's Omniscience evaluation.
52.0 %Specifications from the catalog
Inputtext, image, video, file
Outputtext
Tool callingYes
Structured outputYes
SpeedNot available
First tokenNot available
Maximum output943.7K
Catalog listing date2026-07-16
DeepSWE v1.1 · 113 tasks · mini-swe-agent · cost $2.36 / task · 96 mean steps · 74K mean output tokens. Published by the source 9/22/2026.