Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude 4.1 Opus
52
GLM-5.1
83
Verified leaderboard positions: Claude 4.1 Opus unranked · GLM-5.1 #21
Pick GLM-5.1 if you want the stronger benchmark profile. Claude 4.1 Opus only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+13.6 difference
Claude 4.1 Opus
GLM-5.1
$15 / $75
$1.4 / $4.4
29 t/s
N/A
1.66s
N/A
200K
203K
Pick GLM-5.1 if you want the stronger benchmark profile. Claude 4.1 Opus only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
GLM-5.1 is clearly ahead on the provisional aggregate, 83 to 52. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude 4.1 Opus is also the more expensive model on tokens at $15.00 input / $75.00 output per 1M tokens, versus $1.40 input / $4.40 output per 1M tokens for GLM-5.1. That is roughly 17.0x on output cost alone. GLM-5.1 is the reasoning model in the pair, while Claude 4.1 Opus 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-5.1 gives you the larger context window at 203K, compared with 200K for Claude 4.1 Opus.
GLM-5.1 is ahead on BenchLM's provisional leaderboard, 83 to 52.
Claude 4.1 Opus has the edge for coding in this comparison, averaging 74.5 versus 60.9. GLM-5.1 stays close enough that the answer can still flip depending on your workload.
Estimates at 50,000 req/day · 1000 tokens/req average.
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