Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.1
83
GPT-4.1 nano
27
Verified leaderboard positions: GLM-5.1 #21 · GPT-4.1 nano unranked
Pick GLM-5.1 if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Knowledge
+2.0 difference
GLM-5.1
GPT-4.1 nano
$1.4 / $4.4
$0.1 / $0.4
N/A
181 t/s
N/A
0.63s
203K
1M
Pick GLM-5.1 if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
GLM-5.1 is clearly ahead on the provisional aggregate, 83 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5.1's sharpest advantage is in knowledge, where it averages 52.3 against 50.3.
GLM-5.1 is also the more expensive model on tokens at $1.40 input / $4.40 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 11.0x on output cost alone. GLM-5.1 is the reasoning model in the pair, while GPT-4.1 nano 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. GPT-4.1 nano gives you the larger context window at 1M, compared with 203K for GLM-5.1.
GLM-5.1 is ahead on BenchLM's provisional leaderboard, 83 to 27.
GLM-5.1 has the edge for knowledge tasks in this comparison, averaging 52.3 versus 50.3. GPT-4.1 nano 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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