Head-to-head comparison across 4benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-4.7
68
MAI-Thinking-1
65
Verified leaderboard positions: GLM-4.7 unranked · MAI-Thinking-1 #23
Pick GLM-4.7 if you want the stronger benchmark profile. MAI-Thinking-1 only becomes the better choice if knowledge is the priority or you need the larger 256K context window.
Agentic
+0.7 difference
Coding
+0.4 difference
Knowledge
+9.3 difference
Math
+1.3 difference
GLM-4.7
MAI-Thinking-1
$0 / $0
N/A
82 t/s
N/A
1.10s
N/A
200K
256K
Pick GLM-4.7 if you want the stronger benchmark profile. MAI-Thinking-1 only becomes the better choice if knowledge is the priority or you need the larger 256K context window.
GLM-4.7 has the cleaner provisional overall profile here, landing at 68 versus 65. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
MAI-Thinking-1 gives you the larger context window at 256K, compared with 200K for GLM-4.7.
GLM-4.7 is ahead on BenchLM's provisional leaderboard, 68 to 65. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 41% and 46%.
MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 69.9 versus 60.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
MAI-Thinking-1 has the edge for coding in this comparison, averaging 71 versus 70.6. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
MAI-Thinking-1 has the edge for math in this comparison, averaging 97 versus 95.7. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
MAI-Thinking-1 has the edge for agentic tasks in this comparison, averaging 46 versus 45.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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