LFM2.5-VL-450M vs o1-pro

Pick o1-pro 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.

o1-pro is clearly ahead on the provisional aggregate, 44 to 33. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

o1-pro's sharpest advantage is in knowledge, where it averages 79 against 21.6. The single biggest benchmark swing on the page is GPQA, 25.7% to 79%.

o1-pro is also the more expensive model on tokens at $150.00 input / $600.00 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. o1-pro 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. o1-pro gives you the larger context window at 200K, compared with 128K for LFM2.5-VL-450M.