Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V3
35
MAI-Thinking-1
65
Verified leaderboard positions: DeepSeek V3 unranked · MAI-Thinking-1 #23
Pick MAI-Thinking-1 if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if instruction following is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+31.8 difference
Knowledge
+0.1 difference
Inst. Following
+1.1 difference
DeepSeek V3
MAI-Thinking-1
$0.27 / $1.1
N/A
N/A
N/A
N/A
N/A
128K
256K
Pick MAI-Thinking-1 if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if instruction following is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
MAI-Thinking-1 is clearly ahead on the provisional aggregate, 65 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MAI-Thinking-1's sharpest advantage is in coding, where it averages 71 against 39.2. The single biggest benchmark swing on the page is LiveCodeBench, 37.6% to 87.7%. DeepSeek V3 does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
MAI-Thinking-1 is the reasoning model in the pair, while DeepSeek V3 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. MAI-Thinking-1 gives you the larger context window at 256K, compared with 128K for DeepSeek V3.
MAI-Thinking-1 is ahead on BenchLM's provisional leaderboard, 65 to 35. The biggest single separator in this matchup is LiveCodeBench, where the scores are 37.6% and 87.7%.
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 70 versus 69.9. 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 39.2. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
DeepSeek V3 has the edge for instruction following in this comparison, averaging 86.1 versus 85. MAI-Thinking-1 stays close enough that the answer can still flip depending on your workload.
Estimates at 50,000 req/day · 1000 tokens/req average.
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