Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-4.1 and GPT-4o mini finish on the same overall score, so this is less about a single winner and more about where the edge shows up. The headline says tie; the benchmark table is where the real choice happens.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.15 input / $0.60 output per 1M tokens for GPT-4o mini. That is roughly 13.3x on output cost alone. GPT-4.1 gives you the larger context window at 1M, compared with 128K for GPT-4o mini.
Treat this as a split decision. GPT-4.1 makes more sense if you need the larger 1M context window; GPT-4o mini is the better fit if coding is the priority or you want the cheaper token bill.
GPT-4.1
78.3
GPT-4o mini
82
GPT-4.1
54.6
GPT-4o mini
87.2
GPT-4.1 and GPT-4o mini are tied on overall score, so the right pick depends on which category matters most for your use case.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 78.3. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for coding in this comparison, averaging 87.2 versus 54.6. GPT-4.1 stays close enough that the answer can still flip depending on your workload.
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