Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 Pro 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-5.2 Pro's sharpest advantage is in coding, where it averages 84.8 against 7.2. The single biggest benchmark swing on the page is SWE-bench Pro, 89 to 6.
GPT-5.2 Pro is also the more expensive model on tokens at $25.00 input / $150.00 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-5.2 Pro 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-5.2 Pro gives you the larger context window at 400K, compared with 32K for LFM2.5-1.2B-Instruct.
Pick GPT-5.2 Pro 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-5.2 Pro
85.9
LFM2.5-1.2B-Instruct
25.7
GPT-5.2 Pro
84.8
LFM2.5-1.2B-Instruct
7.2
GPT-5.2 Pro
96
LFM2.5-1.2B-Instruct
32.4
GPT-5.2 Pro
95.2
LFM2.5-1.2B-Instruct
32.1
GPT-5.2 Pro
81.5
LFM2.5-1.2B-Instruct
26
GPT-5.2 Pro
95
LFM2.5-1.2B-Instruct
80
GPT-5.2 Pro
93.4
LFM2.5-1.2B-Instruct
60.7
GPT-5.2 Pro
98.2
LFM2.5-1.2B-Instruct
37
GPT-5.2 Pro is ahead overall, 90 to 30. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 89 and 6.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 26. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for coding in this comparison, averaging 84.8 versus 7.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro 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-5.2 Pro has the edge for reasoning in this comparison, averaging 95.2 versus 32.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for agentic tasks in this comparison, averaging 85.9 versus 25.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 96 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for instruction following in this comparison, averaging 95 versus 80. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multilingual tasks in this comparison, averaging 93.4 versus 60.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.