Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.2
79
LFM2.5-VL-450M
33
Pick GPT-5.2 if you want the stronger benchmark profile. LFM2.5-VL-450M 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.
Knowledge
+70.8 difference
GPT-5.2
LFM2.5-VL-450M
$2 / $8
$0 / $0
73 t/s
N/A
130.34s
N/A
400K
128K
Pick GPT-5.2 if you want the stronger benchmark profile. LFM2.5-VL-450M 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 is clearly ahead on the provisional aggregate, 79 to 33. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2's sharpest advantage is in knowledge, where it averages 92.4 against 21.6. The single biggest benchmark swing on the page is GPQA, 92.4% to 25.7%.
GPT-5.2 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for LFM2.5-VL-450M. That is roughly Infinityx on output cost alone. GPT-5.2 is the reasoning model in the pair, while LFM2.5-VL-450M 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 gives you the larger context window at 400K, compared with 128K for LFM2.5-VL-450M.
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 79 to 33. The biggest single separator in this matchup is GPQA, where the scores are 92.4% and 25.7%.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 21.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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