Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Mythos 5
99
GLM-5
67
Verified leaderboard positions: Claude Mythos 5 #1 · GLM-5 #23
Pick Claude Mythos 5 if you want the stronger benchmark profile. GLM-5 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Agentic
+30.8 difference
Coding
+22.7 difference
Knowledge
+3.9 difference
Claude Mythos 5
GLM-5
$10 / $50
$1 / $3.2
N/A
74 t/s
N/A
1.64s
1M+
200K
Pick Claude Mythos 5 if you want the stronger benchmark profile. GLM-5 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Claude Mythos 5 is clearly ahead on the provisional aggregate, 99 to 67. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Mythos 5's sharpest advantage is in agentic, where it averages 87 against 56.2. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 88% to 56.2%.
Claude Mythos 5 is also the more expensive model on tokens at $10.00 input / $50.00 output per 1M tokens, versus $1.00 input / $3.20 output per 1M tokens for GLM-5. That is roughly 15.6x on output cost alone. Claude Mythos 5 is the reasoning model in the pair, while GLM-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. Claude Mythos 5 gives you the larger context window at 1M+, compared with 200K for GLM-5.
Claude Mythos 5 is ahead on BenchLM's provisional leaderboard, 99 to 67. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 88% and 56.2%.
Claude Mythos 5 has the edge for knowledge tasks in this comparison, averaging 74.6 versus 70.7. Inside this category, HLE is the benchmark that creates the most daylight between them.
Claude Mythos 5 has the edge for coding in this comparison, averaging 85.9 versus 63.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Claude Mythos 5 has the edge for agentic tasks in this comparison, averaging 87 versus 56.2. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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