Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-OSS 20B is clearly ahead on the aggregate, 35 to 30. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-OSS 20B's sharpest advantage is in agentic, where it averages 35.4 against 25.7. The single biggest benchmark swing on the page is LongBench v2, 48 to 34. LFM2.5-1.2B-Instruct does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
GPT-OSS 20B gives you the larger context window at 128K, compared with 32K for LFM2.5-1.2B-Instruct.
Pick GPT-OSS 20B if you want the stronger benchmark profile. LFM2.5-1.2B-Instruct only becomes the better choice if instruction following is the priority.
GPT-OSS 20B
35.4
LFM2.5-1.2B-Instruct
25.7
GPT-OSS 20B
14.5
LFM2.5-1.2B-Instruct
7.2
GPT-OSS 20B
36
LFM2.5-1.2B-Instruct
32.4
GPT-OSS 20B
40.4
LFM2.5-1.2B-Instruct
32.1
GPT-OSS 20B
29
LFM2.5-1.2B-Instruct
26
GPT-OSS 20B
67
LFM2.5-1.2B-Instruct
80
GPT-OSS 20B
59.7
LFM2.5-1.2B-Instruct
60.7
GPT-OSS 20B
43.1
LFM2.5-1.2B-Instruct
37
GPT-OSS 20B is ahead overall, 35 to 30. The biggest single separator in this matchup is LongBench v2, where the scores are 48 and 34.
GPT-OSS 20B has the edge for knowledge tasks in this comparison, averaging 29 versus 26. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-OSS 20B has the edge for coding in this comparison, averaging 14.5 versus 7.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-OSS 20B has the edge for math in this comparison, averaging 43.1 versus 37. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-OSS 20B has the edge for reasoning in this comparison, averaging 40.4 versus 32.1. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
GPT-OSS 20B has the edge for agentic tasks in this comparison, averaging 35.4 versus 25.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-OSS 20B has the edge for multimodal and grounded tasks in this comparison, averaging 36 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
LFM2.5-1.2B-Instruct has the edge for instruction following in this comparison, averaging 80 versus 67. Inside this category, IFEval is the benchmark that creates the most daylight between them.
LFM2.5-1.2B-Instruct has the edge for multilingual tasks in this comparison, averaging 60.7 versus 59.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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