Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-4.7
69
Muse Spark
82
Pick Muse Spark if you want the stronger benchmark profile. GLM-4.7 only becomes the better choice if knowledge is the priority.
Agentic
+13.7 difference
Coding
+8.9 difference
Knowledge
+10.2 difference
GLM-4.7
Muse Spark
$0 / $0
N/A
82 t/s
N/A
1.10s
N/A
200K
262K
Pick Muse Spark if you want the stronger benchmark profile. GLM-4.7 only becomes the better choice if knowledge is the priority.
Muse Spark is clearly ahead on the provisional aggregate, 82 to 69. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Muse Spark's sharpest advantage is in agentic, where it averages 59 against 45.3. The single biggest benchmark swing on the page is HLE, 24.8% to 50.4%. GLM-4.7 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Muse Spark gives you the larger context window at 262K, compared with 200K for GLM-4.7.
Muse Spark is ahead on BenchLM's provisional leaderboard, 82 to 69. The biggest single separator in this matchup is HLE, where the scores are 24.8% and 50.4%.
GLM-4.7 has the edge for knowledge tasks in this comparison, averaging 60.6 versus 50.4. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
GLM-4.7 has the edge for coding in this comparison, averaging 70.6 versus 61.7. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
Muse Spark has the edge for agentic tasks in this comparison, averaging 59 versus 45.3. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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