Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-4.7
70
o1
58
Pick GLM-4.7 if you want the stronger benchmark profile. o1 only becomes the better choice if knowledge is the priority.
Knowledge
+15.1 difference
GLM-4.7
o1
$0 / $0
$15 / $60
82 t/s
98 t/s
1.10s
32.29s
200K
200K
Pick GLM-4.7 if you want the stronger benchmark profile. o1 only becomes the better choice if knowledge is the priority.
GLM-4.7 is clearly ahead on the provisional aggregate, 70 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 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 58. The biggest single separator in this matchup is GPQA, where the scores are 85.7% and 75.7%.
o1 has the edge for knowledge tasks in this comparison, averaging 75.7 versus 60.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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