Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro Base
41
GLM-5.2
94
Verified leaderboard positions: DeepSeek V4 Pro Base unranked · GLM-5.2 #9
Pick GLM-5.2 if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+3.8 difference
DeepSeek V4 Pro Base
GLM-5.2
$null / $null
$1.4 / $4.4
N/A
N/A
N/A
N/A
1M
1M
Pick GLM-5.2 if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
GLM-5.2 is clearly ahead on the provisional aggregate, 94 to 41. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5.2's sharpest advantage is in knowledge, where it averages 67.2 against 63.4.
GLM-5.2 is the reasoning model in the pair, while DeepSeek V4 Pro Base 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-5.2 is ahead on BenchLM's provisional leaderboard, 94 to 41.
GLM-5.2 has the edge for knowledge tasks in this comparison, averaging 67.2 versus 63.4. DeepSeek V4 Pro Base stays close enough that the answer can still flip depending on your workload.
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