Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.1
83
GPT-5.4 mini
71
Verified leaderboard positions: GLM-5.1 #21 · GPT-5.4 mini unranked
Pick GLM-5.1 if you want the stronger benchmark profile. GPT-5.4 mini only becomes the better choice if knowledge is the priority or you need the larger 400K context window.
Agentic
+0.3 difference
Knowledge
+5.1 difference
GLM-5.1
GPT-5.4 mini
$1.4 / $4.4
$0.75 / $4.5
N/A
201 t/s
N/A
3.85s
203K
400K
Pick GLM-5.1 if you want the stronger benchmark profile. GPT-5.4 mini only becomes the better choice if knowledge is the priority or you need the larger 400K context window.
GLM-5.1 is clearly ahead on the provisional aggregate, 83 to 71. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 mini is also the more expensive model on tokens at $0.75 input / $4.50 output per 1M tokens, versus $1.40 input / $4.40 output per 1M tokens for GLM-5.1. GPT-5.4 mini gives you the larger context window at 400K, compared with 203K for GLM-5.1.
GLM-5.1 is ahead on BenchLM's provisional leaderboard, 83 to 71. The biggest single separator in this matchup is HLE, where the scores are 52.3% and 41.5%.
GPT-5.4 mini has the edge for knowledge tasks in this comparison, averaging 57.4 versus 52.3. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.4 mini has the edge for agentic tasks in this comparison, averaging 65.6 versus 65.3. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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