Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GLM-5 is clearly ahead on the aggregate, 54 to 25. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5's sharpest advantage is in reasoning, where it averages 82.9 against 24.9. The single biggest benchmark swing on the page is SimpleQA, 24.9% to 84%. DeepSeek V3 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GLM-5 gives you the larger context window at 200K, compared with 128K for DeepSeek V3.
Pick GLM-5 if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if knowledge is the priority.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
DeepSeek V3
42
GLM-5
78.9
Benchmark data for this category is coming soon.
DeepSeek V3
24.9
GLM-5
82.9
DeepSeek V3
69.6
GLM-5
60.2
Benchmark data for this category is coming soon.
Benchmark data for this category is coming soon.
DeepSeek V3
90.2
GLM-5
87
GLM-5 is ahead overall, 54 to 25. The biggest single separator in this matchup is SimpleQA, where the scores are 24.9% and 84%.
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 69.6 versus 60.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GLM-5 has the edge for coding in this comparison, averaging 78.9 versus 42. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
DeepSeek V3 has the edge for math in this comparison, averaging 90.2 versus 87. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GLM-5 has the edge for reasoning in this comparison, averaging 82.9 versus 24.9. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
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