Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-4.7
70
o1-pro
29
Pick GLM-4.7 if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority.
Knowledge
+18.4 difference
GLM-4.7
o1-pro
$0 / $0
$150 / $600
82 t/s
N/A
1.10s
N/A
200K
200K
Pick GLM-4.7 if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority.
GLM-4.7 is clearly ahead on the provisional aggregate, 70 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 $0.00 input / $0.00 output per 1M tokens for GLM-4.7. That is roughly Infinityx on output cost alone.
GLM-4.7 is ahead on BenchLM's provisional leaderboard, 70 to 29. The biggest single separator in this matchup is GPQA, where the scores are 85.7% and 79%.
o1-pro has the edge for knowledge tasks in this comparison, averaging 79 versus 60.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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