Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GLM-5 (Reasoning) is clearly ahead on the aggregate, 78 to 65. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5 (Reasoning)'s sharpest advantage is in coding, where it averages 62.5 against 42.4. The single biggest benchmark swing on the page is AIME 2023, 98 to 72. Seed 1.6 does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
Seed 1.6 gives you the larger context window at 256K, compared with 200K for GLM-5 (Reasoning).
Pick GLM-5 (Reasoning) if you want the stronger benchmark profile. Seed 1.6 only becomes the better choice if multimodal & grounded is the priority or you need the larger 256K context window.
GLM-5 (Reasoning)
78.3
Seed 1.6
62.3
GLM-5 (Reasoning)
62.5
Seed 1.6
42.4
GLM-5 (Reasoning)
78.5
Seed 1.6
79.6
GLM-5 (Reasoning)
88.9
Seed 1.6
74.5
GLM-5 (Reasoning)
72
Seed 1.6
56.4
GLM-5 (Reasoning)
92
Seed 1.6
87
GLM-5 (Reasoning)
86.4
Seed 1.6
83.4
GLM-5 (Reasoning)
94.4
Seed 1.6
75.9
GLM-5 (Reasoning) is ahead overall, 78 to 65. The biggest single separator in this matchup is AIME 2023, where the scores are 98 and 72.
GLM-5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 72 versus 56.4. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for coding in this comparison, averaging 62.5 versus 42.4. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for math in this comparison, averaging 94.4 versus 75.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for reasoning in this comparison, averaging 88.9 versus 74.5. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for agentic tasks in this comparison, averaging 78.3 versus 62.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Seed 1.6 has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 versus 78.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for instruction following in this comparison, averaging 92 versus 87. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for multilingual tasks in this comparison, averaging 86.4 versus 83.4. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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