Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.5
77
GLM-5.1
83
Verified leaderboard positions: Claude Opus 4.5 #9 · GLM-5.1 #21
Pick GLM-5.1 if you want the stronger benchmark profile. Claude Opus 4.5 only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Agentic
+2.8 difference
Coding
+5.0 difference
Knowledge
+13.9 difference
Claude Opus 4.5
GLM-5.1
$5 / $25
$1.4 / $4.4
46 t/s
N/A
1.01s
N/A
200K
203K
Pick GLM-5.1 if you want the stronger benchmark profile. Claude Opus 4.5 only becomes the better choice if knowledge 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 77. 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 agentic, where it averages 65.3 against 62.5. The single biggest benchmark swing on the page is HLE, 30.8% to 52.3%. Claude Opus 4.5 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude Opus 4.5 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $1.40 input / $4.40 output per 1M tokens for GLM-5.1. That is roughly 5.7x on output cost alone. GLM-5.1 is the reasoning model in the pair, while Claude Opus 4.5 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 Opus 4.5.
GLM-5.1 is ahead on BenchLM's provisional leaderboard, 83 to 77. The biggest single separator in this matchup is HLE, where the scores are 30.8% and 52.3%.
Claude Opus 4.5 has the edge for knowledge tasks in this comparison, averaging 66.2 versus 52.3. Inside this category, HLE is the benchmark that creates the most daylight between them.
Claude Opus 4.5 has the edge for coding in this comparison, averaging 65.9 versus 60.9. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GLM-5.1 has the edge for agentic tasks in this comparison, averaging 65.3 versus 62.5. 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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