Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4o mini is clearly ahead on the aggregate, 52 to 30. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4o mini's sharpest advantage is in coding, where it averages 65 against 7.2. The single biggest benchmark swing on the page is HumanEval, 87.2 to 14.
GPT-4o mini is also the more expensive model on tokens at $0.15 input / $0.60 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-4o mini gives you the larger context window at 128K, compared with 32K for LFM2.5-1.2B-Instruct.
Pick GPT-4o mini if you want the stronger benchmark profile. LFM2.5-1.2B-Instruct only becomes the better choice if you want the cheaper token bill.
GPT-4o mini
50.9
LFM2.5-1.2B-Instruct
25.7
GPT-4o mini
65
LFM2.5-1.2B-Instruct
7.2
GPT-4o mini
60.2
LFM2.5-1.2B-Instruct
32.4
GPT-4o mini
49.4
LFM2.5-1.2B-Instruct
32.1
GPT-4o mini
62
LFM2.5-1.2B-Instruct
26
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
GPT-4o mini
74.7
LFM2.5-1.2B-Instruct
60.7
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
GPT-4o mini is ahead overall, 52 to 30. The biggest single separator in this matchup is HumanEval, where the scores are 87.2 and 14.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 62 versus 26. 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 65 versus 7.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for reasoning in this comparison, averaging 49.4 versus 32.1. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for agentic tasks in this comparison, averaging 50.9 versus 25.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for multimodal and grounded tasks in this comparison, averaging 60.2 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for multilingual tasks in this comparison, averaging 74.7 versus 60.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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