Meta: Muse Spark 1.3
Meta's mid-tier model. Long-context specialist with 1.0M window.
Scores by test
Methodology →What you need to know
Meta: Muse Spark 1.3 is defined by its high performance in complex reasoning and long-context processing. With a 1.0M token context window and perfect scores in strategic analysis, agentic planning, and creative problem solving, it is designed for deep architectural tasks and large-scale data synthesis. Its ability to maintain faithfulness and persona consistency across these long windows makes it a strong candidate for complex agentic workflows.
The model excels at generating structured output and handling tabular data, both scoring 5/5. However, it struggles with classification and safety calibration. The low safety score indicates a tendency to over-refuse benign requests, which may introduce friction in user-facing applications.
At a blended cost of $3.50/MTok, the model is priced as a mid-to-high tier option. While it offers top-tier reasoning and structural precision, the cost is higher than basic utility models, making it a value proposition specifically for developers who require high-fidelity structured data and massive context windows.
Use this model if your project requires agentic planning, complex strategic analysis, or the processing of extremely large documents. Skip this model if your primary use case is simple classification or if your application cannot tolerate high rates of false-positive refusals.
Strengths — Top 3
Relative weaknesses — Bottom 3
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