MuSR A
AI benchmark · Reasoning
What is MuSR?
A dataset for evaluating language models on multistep soft reasoning tasks specified in natural language narratives. Tests the ability to perform complex, structured reasoning.
Tier A
Widely used: a lab reports it, or 50 or more models are scored on it.
How much stands behind a tier: usage, who backs it, a confirmed line from its own site or paper, and a clear read on X. High with three of the four, medium with two, low otherwise.
- 3835 models scored
- model counts only from community leaderboards
- in curated RL directories (2 pts)
On X · unclear, low buzz, from 1 post about MuSR in the last month
Barely discussed; the one engaged post is about a quantized Qwen model for local agents and mentions MuSR only incidentally, if at all.
How we got to tier A
- Adoption: 3835 models scored; model counts only from community leaderboards. Tier A.
- On X: unclear, low buzz. “Barely discussed; the one engaged post is about a quantized Qwen model for local agents and mentions MuSR only incidentally, if at all.” No move.
- In curated RL directories: 2 points, a floor of C.
- Not yet confirmed by a line from its own site or paper.
A clear view on X moves a tier one step up or down; most entries don't move. How tiers work.
Not on the map yet: no line from its own site or paper places it in a domain.
Next: browse all benchmarks. Entry from the RL Research daily scrape of public sources, 2026-10-11 snapshot.