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 53. 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 24.7. The single biggest benchmark swing on the page is SWE-bench Verified, 62 to 22.
GLM-5 (Reasoning) is the reasoning model in the pair, while Seed-2.0-Mini 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. Seed-2.0-Mini 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-2.0-Mini only becomes the better choice if you need the larger 256K context window or you would rather avoid the extra latency and token burn of a reasoning model.
GLM-5 (Reasoning)
78.3
Seed-2.0-Mini
46.2
GLM-5 (Reasoning)
62.5
Seed-2.0-Mini
24.7
GLM-5 (Reasoning)
78.5
Seed-2.0-Mini
73.1
GLM-5 (Reasoning)
88.9
Seed-2.0-Mini
64.8
GLM-5 (Reasoning)
72
Seed-2.0-Mini
44.6
GLM-5 (Reasoning)
92
Seed-2.0-Mini
80
GLM-5 (Reasoning)
86.4
Seed-2.0-Mini
71.8
GLM-5 (Reasoning)
94.4
Seed-2.0-Mini
65.1
GLM-5 (Reasoning) is ahead overall, 78 to 53. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 62 and 22.
GLM-5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 72 versus 44.6. 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 24.7. Inside this category, SWE-bench Verified 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 65.1. 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 64.8. 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 46.2. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for multimodal and grounded tasks in this comparison, averaging 78.5 versus 73.1. Inside this category, OfficeQA 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 80. 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 71.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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