Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Sibling matchup inside the GPT-5.4 family.
GPT-5.4 mini
71
GPT-5.4 Pro
91
GPT-5.4 mini makes more sense if knowledge is the priority or you want the cheaper token bill, while GPT-5.4 Pro is the cleaner fit if agentic is the priority or you need the larger 1.05M context window.
Agentic
+23.7 difference
Knowledge
+8.4 difference
Multimodal
+17.4 difference
GPT-5.4 mini
GPT-5.4 Pro
$0.75 / $4.5
$30 / $180
201 t/s
74 t/s
3.85s
151.79s
400K
1.05M
GPT-5.4 mini makes more sense if knowledge is the priority or you want the cheaper token bill, while GPT-5.4 Pro is the cleaner fit if agentic is the priority or you need the larger 1.05M context window.
GPT-5.4 mini and GPT-5.4 Pro sit in the same GPT-5.4 family. This page is less about two unrelated model lineages and more about how the siblings trade off on benchmark shape, token costs, and practical limits like context window.
GPT-5.4 Pro is clearly ahead on the provisional aggregate, 91 to 71. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 Pro's sharpest advantage is in agentic, where it averages 89.3 against 65.6. The single biggest benchmark swing on the page is MMMU-Pro, 76.6% to 94%. GPT-5.4 mini does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-5.4 Pro is also the more expensive model on tokens at $30.00 input / $180.00 output per 1M tokens, versus $0.75 input / $4.50 output per 1M tokens for GPT-5.4 mini. That is roughly 40.0x on output cost alone. GPT-5.4 Pro gives you the larger context window at 1.05M, compared with 400K for GPT-5.4 mini.
GPT-5.4 mini and GPT-5.4 Pro are sibling variants in the GPT-5.4 family, so the right pick depends on whether you value the better benchmark line, cheaper tokens, or the larger context window. GPT-5.4 Pro is ahead on BenchLM's provisional leaderboard 91 to 71.
GPT-5.4 mini has the edge for knowledge tasks in this comparison, averaging 57.4 versus 49. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.4 Pro has the edge for agentic tasks in this comparison, averaging 89.3 versus 65.6. GPT-5.4 mini stays close enough that the answer can still flip depending on your workload.
GPT-5.4 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 94 versus 76.6. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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