Head-to-head comparison across 4benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4
88
GPT-5.5
89
Verified leaderboard positions: GPT-5.4 #13 · GPT-5.5 #2
Pick GPT-5.5 if you want the stronger benchmark profile. GPT-5.4 only becomes the better choice if you want the cheaper token bill or you need the larger 1.05M context window.
Agentic
+4.8 difference
Coding
+0.9 difference
Knowledge
+0.3 difference
Multimodal
+0.4 difference
GPT-5.4
GPT-5.5
$2.5 / $15
$5 / $30
74 t/s
N/A
151.79s
N/A
1.05M
1M
Pick GPT-5.5 if you want the stronger benchmark profile. GPT-5.4 only becomes the better choice if you want the cheaper token bill or you need the larger 1.05M context window.
GPT-5.5 finishes one point ahead on BenchLM's provisional leaderboard, 89 to 88. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
GPT-5.5's sharpest advantage is in agentic, where it averages 81.8 against 77. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 75.1% to 82.7%.
GPT-5.5 is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $2.50 input / $15.00 output per 1M tokens for GPT-5.4. That is roughly 2.0x on output cost alone. GPT-5.4 gives you the larger context window at 1.05M, compared with 1M for GPT-5.5.
GPT-5.5 is ahead on BenchLM's provisional leaderboard, 89 to 88. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 75.1% and 82.7%.
GPT-5.5 has the edge for knowledge tasks in this comparison, averaging 66.4 versus 66.1. Inside this category, HLE w/o tools is the benchmark that creates the most daylight between them.
GPT-5.5 has the edge for coding in this comparison, averaging 58.6 versus 57.7. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.5 has the edge for agentic tasks in this comparison, averaging 81.8 versus 77. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.5 has the edge for multimodal and grounded tasks in this comparison, averaging 69 versus 68.6. Inside this category, MMMU-Pro w/ Python is the benchmark that creates the most daylight between them.
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