Meta's Muse Spark 1.2 is a multimodal reasoning model for complex agentic and coding tasks, with tool calling, structured output, and a one-million-token context window.
Added Aug 5, 2026
Context Window
1.0M
Max Output
65.5K
Avg output tokens (7d)
1.3K tokens
Input Price (Auto)
$1.25/1M
Output Price (Auto)
$4.25/1M
Cache Read (Auto)
$0.15/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
46.8
Coding Index
72.2
Agentic Index
44.2
Reasoning
GPQA Diamond
Graduate-level scientific reasoning
90.4%
Better than 90% of models compared
HLE
Humanity's Last Exam
45.5%
Better than 95% of models compared
AA-LCR
Long context reasoning evaluation
79.0%
Better than 86% of models compared
GDPval-AA
Economically valuable tasks
51.4%
CritPt
Research-level physics reasoning
17.7%
Coding
SciCode
Python programming for scientific computing
57.4%
Better than 89% of models compared
Knowledge
AA-Omniscience Accuracy
Proportion of correctly answered questions
45.4%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
33.3%
Last updated Sep 7, 2026
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