Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 2.5 Pro
67
GPT-5.3 Codex
89
Pick GPT-5.3 Codex if you want the stronger benchmark profile. Gemini 2.5 Pro only becomes the better choice if coding is the priority or you want the cheaper token bill.
Coding
+0.7 difference
Gemini 2.5 Pro
GPT-5.3 Codex
$1.25 / $5
$2.5 / $10
117 t/s
79 t/s
21.19s
88.26s
1M
400K
Pick GPT-5.3 Codex if you want the stronger benchmark profile. Gemini 2.5 Pro 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, 89 to 67. 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 $2.50 input / $10.00 output per 1M tokens, versus $1.25 input / $5.00 output per 1M tokens for Gemini 2.5 Pro. That is roughly 2.0x on output cost alone. GPT-5.3 Codex is the reasoning model in the pair, while Gemini 2.5 Pro 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. Gemini 2.5 Pro 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 67. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 63.8% and 85%.
Gemini 2.5 Pro has the edge for coding in this comparison, averaging 63.8 versus 63.1. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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