Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.3 Codex
86
MAI-Thinking-1
65
Verified leaderboard positions: GPT-5.3 Codex unranked · MAI-Thinking-1 #23
Pick GPT-5.3 Codex if you want the stronger benchmark profile. MAI-Thinking-1 only becomes the better choice if coding is the priority.
Agentic
+25.5 difference
Coding
+7.9 difference
GPT-5.3 Codex
MAI-Thinking-1
$1.75 / $14
N/A
79 t/s
N/A
88.26s
N/A
400K
256K
Pick GPT-5.3 Codex if you want the stronger benchmark profile. MAI-Thinking-1 only becomes the better choice if coding is the priority.
GPT-5.3 Codex is clearly ahead on the provisional aggregate, 86 to 65. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3 Codex's sharpest advantage is in agentic, where it averages 71.5 against 46. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 77.3% to 46%. MAI-Thinking-1 does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.3 Codex gives you the larger context window at 400K, compared with 256K for MAI-Thinking-1.
GPT-5.3 Codex is ahead on BenchLM's provisional leaderboard, 86 to 65. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 77.3% and 46%.
MAI-Thinking-1 has the edge for coding in this comparison, averaging 71 versus 63.1. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for agentic tasks in this comparison, averaging 71.5 versus 46. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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