Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro (High)
83
GLM-5
67
Verified leaderboard positions: DeepSeek V4 Pro (High) #6 · GLM-5 #17
Pick DeepSeek V4 Pro (High) if you want the stronger benchmark profile. GLM-5 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Agentic
+13.8 difference
Coding
+10.6 difference
Knowledge
+8.1 difference
DeepSeek V4 Pro (High)
GLM-5
$1.74 / $3.48
$1 / $3.2
N/A
74 t/s
N/A
1.64s
1M
200K
Pick DeepSeek V4 Pro (High) if you want the stronger benchmark profile. GLM-5 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
DeepSeek V4 Pro (High) is clearly ahead on the provisional aggregate, 83 to 67. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V4 Pro (High)'s sharpest advantage is in agentic, where it averages 70 against 56.2. The single biggest benchmark swing on the page is HLE, 34.5% to 50.4%. GLM-5 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
DeepSeek V4 Pro (High) is also the more expensive model on tokens at $1.74 input / $3.48 output per 1M tokens, versus $1.00 input / $3.20 output per 1M tokens for GLM-5. DeepSeek V4 Pro (High) 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. DeepSeek V4 Pro (High) gives you the larger context window at 1M, compared with 200K for GLM-5.
DeepSeek V4 Pro (High) is ahead on BenchLM's provisional leaderboard, 83 to 67. The biggest single separator in this matchup is HLE, where the scores are 34.5% and 50.4%.
GLM-5 has the edge for knowledge tasks in this comparison, averaging 70.7 versus 62.6. Inside this category, HLE is the benchmark that creates the most daylight between them.
DeepSeek V4 Pro (High) has the edge for coding in this comparison, averaging 73.8 versus 63.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
DeepSeek V4 Pro (High) has the edge for agentic tasks in this comparison, averaging 70 versus 56.2. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.
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