Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5
67
o1-pro
29
Verified leaderboard positions: GLM-5 #17 · o1-pro unranked
Pick GLM-5 if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Knowledge
+8.3 difference
GLM-5
o1-pro
$1 / $3.2
$150 / $600
74 t/s
N/A
1.64s
N/A
200K
200K
Pick GLM-5 if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
GLM-5 is clearly ahead on the provisional aggregate, 67 to 29. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1-pro is also the more expensive model on tokens at $150.00 input / $600.00 output per 1M tokens, versus $1.00 input / $3.20 output per 1M tokens for GLM-5. That is roughly 187.5x on output cost alone. o1-pro is the reasoning model in the pair, while GLM-5 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use.
GLM-5 is ahead on BenchLM's provisional leaderboard, 67 to 29. The biggest single separator in this matchup is GPQA, where the scores are 86% and 79%.
o1-pro has the edge for knowledge tasks in this comparison, averaging 79 versus 70.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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