Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.3 Codex
89
MiMo-V2.5
74
Pick GPT-5.3 Codex if you want the stronger benchmark profile. MiMo-V2.5 only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Agentic
+5.7 difference
Coding
+7.0 difference
GPT-5.3 Codex
MiMo-V2.5
$2.5 / $10
$0.4 / $2
79 t/s
N/A
88.26s
N/A
400K
1M
Pick GPT-5.3 Codex if you want the stronger benchmark profile. MiMo-V2.5 only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
GPT-5.3 Codex is clearly ahead on the provisional aggregate, 89 to 74. 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 coding, where it averages 63.1 against 56.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 77.3% to 65.8%.
GPT-5.3 Codex is also the more expensive model on tokens at $2.50 input / $10.00 output per 1M tokens, versus $0.40 input / $2.00 output per 1M tokens for MiMo-V2.5. That is roughly 5.0x on output cost alone. MiMo-V2.5 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, 89 to 74. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 77.3% and 65.8%.
GPT-5.3 Codex has the edge for coding in this comparison, averaging 63.1 versus 56.1. Inside this category, SWE-bench Pro 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 65.8. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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