Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V3.2
57
GLM-5
67
Verified leaderboard positions: DeepSeek V3.2 unranked · GLM-5 #21
Pick GLM-5 if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if you want the cheaper token bill.
Coding
+2.3 difference
DeepSeek V3.2
GLM-5
$0.28 / $0.42
$1 / $3.2
35 t/s
74 t/s
3.75s
1.64s
128K
200K
Pick GLM-5 if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if you want the cheaper token bill.
GLM-5 is clearly ahead on the provisional aggregate, 67 to 57. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5's sharpest advantage is in coding, where it averages 63.2 against 60.9. The single biggest benchmark swing on the page is SWE-Rebench, 60.9% to 62.8%.
GLM-5 is also the more expensive model on tokens at $1.00 input / $3.20 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2. That is roughly 7.6x on output cost alone. GLM-5 gives you the larger context window at 200K, compared with 128K for DeepSeek V3.2.
GLM-5 is ahead on BenchLM's provisional leaderboard, 67 to 57. The biggest single separator in this matchup is SWE-Rebench, where the scores are 60.9% and 62.8%.
GLM-5 has the edge for coding in this comparison, averaging 63.2 versus 60.9. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
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