Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.3 Codex
86
MiniMax M3
76
Verified leaderboard positions: GPT-5.3 Codex unranked · MiniMax M3 #12
Pick GPT-5.3 Codex if you want the stronger benchmark profile. MiniMax M3 only becomes the better choice if coding is the priority or you want the cheaper token bill.
Agentic
+0.4 difference
Coding
+3.9 difference
GPT-5.3 Codex
MiniMax M3
$1.75 / $14
$0.3 / $1.2
79 t/s
N/A
88.26s
N/A
400K
1M
Pick GPT-5.3 Codex if you want the stronger benchmark profile. MiniMax M3 only becomes the better choice if coding is the priority or you want the cheaper token bill.
GPT-5.3 Codex is clearly ahead on the provisional aggregate, 86 to 76. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3 Codex is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M3. That is roughly 11.7x on output cost alone. GPT-5.3 Codex is the reasoning model in the pair, while MiniMax M3 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. MiniMax M3 gives you the larger context window at 1M, compared with 400K for GPT-5.3 Codex.
GPT-5.3 Codex is ahead on BenchLM's provisional leaderboard, 86 to 76. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 77.3% and 66%.
MiniMax M3 has the edge for coding in this comparison, averaging 67 versus 63.1. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
MiniMax M3 has the edge for agentic tasks in this comparison, averaging 71.9 versus 71.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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