Meta: Muse Spark 1.1
meta's flagship model. Long-context specialist with 1.0M window.
Scores by test
Methodology →What you need to know
Meta: Muse Spark 1.1 is a top-tier generalist model, ranking 10th out of 125 evaluated models. Its primary differentiator is a near-perfect performance across complex reasoning tasks, specifically in strategic analysis, creative problem solving, and agentic planning. With a 1.0M context window and a perfect score in long-context processing, it is built for high-density data retrieval and complex orchestration.
The model excels at technical precision, achieving a 5/5 in structured output, tool calling, and tabular data handling. This makes it highly reliable for developers building autonomous agents or systems requiring strict schema adherence. However, it shows a relative weakness in simple classification tasks, where it scores a 3/5, suggesting it may be over-engineered for basic labeling or sorting duties.
At a blended cost of $3.50/MTok, this model sits in a premium price bracket. While more expensive than mid-range options, the cost is justified by its versatility and high internal average score of 4.77/5.0. You are paying for high-level reasoning and reliability in complex workflows rather than raw throughput.
Use this model if you are building complex AI agents, processing massive documents, or require flawless structured data output. Skip this model if your primary use case is simple text classification or if you are operating on a tight budget for low-complexity tasks.
Strengths — Top 3
Relative weaknesses — Bottom 3
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