#15Meta· released 2026-10-15

Meta: Muse Spark Open.

Muse Spark Open is a coding-optimized open-weight model. Trained specifically for agentic coding workflows, it delivers higher first-attempt accuracy, reliable tool calling, and deep codebase understanding across the repos developers...

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Context
1.0M
Input $/1M
$1.25
Output $/1M
$4.25
Modality
text · image · video · file · audio
Arena Elo
1572
LMArena — human blind votes
AA Index
59.0
Artificial Analysis composite
LiveBench
79.3
Contamination-resistant
GPQA
84.2%
Grad-level science reasoning
MMLU-Pro
84.1%
Broad knowledge
SWE-bench
73.7%
Real GitHub bugs (Verified)
Terminal-Bench
57.8%
Agentic shell tasks
ARC-AGI
28.8%
Abstract reasoning
Aider Polyglot
83.2%
Multi-language code editing
Speed
73 tok/s
Median output speed

Profile

Meta: Muse Spark Open is Meta's entry at position #15 on the current aggregated leaderboard. Its strongest signals are graduate-level science reasoning, real-world software engineering, unattended agentic work, and very long context. Every figure below is aggregated from the public sources listed on the homepage and refreshed on each pipeline run.

The score spread is comparatively complete for this model, but the standing advice still applies: treat gaps of a few points as ties and validate on your own workload before committing.

How this model's position is computed is documented in the methodology; what each benchmark actually measures is in the benchmark guide. See a figure that disagrees with its source? Report it — accepted corrections apply on the next refresh.

Nearby on the leaderboard