Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.4 is clearly ahead on the aggregate, 90 to 30. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4's sharpest advantage is in coding, where it averages 84.5 against 7.2. The single biggest benchmark swing on the page is HumanEval, 95 to 14.
GPT-5.4 is also the more expensive model on tokens at $2.50 input / $15.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for LFM2.5-1.2B-Instruct. That is roughly Infinityx on output cost alone. GPT-5.4 is the reasoning model in the pair, while LFM2.5-1.2B-Instruct 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. GPT-5.4 gives you the larger context window at 1.05M, compared with 32K for LFM2.5-1.2B-Instruct.
Pick GPT-5.4 if you want the stronger benchmark profile. LFM2.5-1.2B-Instruct only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.4
87.8
LFM2.5-1.2B-Instruct
25.7
GPT-5.4
84.5
LFM2.5-1.2B-Instruct
7.2
GPT-5.4
95.5
LFM2.5-1.2B-Instruct
32.4
GPT-5.4
95.8
LFM2.5-1.2B-Instruct
32.1
GPT-5.4
82.6
LFM2.5-1.2B-Instruct
26
GPT-5.4
96
LFM2.5-1.2B-Instruct
80
GPT-5.4
94.7
LFM2.5-1.2B-Instruct
60.7
GPT-5.4
98.2
LFM2.5-1.2B-Instruct
37
GPT-5.4 is ahead overall, 90 to 30. The biggest single separator in this matchup is HumanEval, where the scores are 95 and 14.
GPT-5.4 has the edge for knowledge tasks in this comparison, averaging 82.6 versus 26. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-5.4 has the edge for coding in this comparison, averaging 84.5 versus 7.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-5.4 has the edge for math in this comparison, averaging 98.2 versus 37. Inside this category, HMMT Feb 2023 is the benchmark that creates the most daylight between them.
GPT-5.4 has the edge for reasoning in this comparison, averaging 95.8 versus 32.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.4 has the edge for agentic tasks in this comparison, averaging 87.8 versus 25.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.4 has the edge for multimodal and grounded tasks in this comparison, averaging 95.5 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.4 has the edge for instruction following in this comparison, averaging 96 versus 80. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.4 has the edge for multilingual tasks in this comparison, averaging 94.7 versus 60.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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