Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4 nano
61
LFM2.5-VL-450M
33
Pick GPT-5.4 nano 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
+31.6 difference
GPT-5.4 nano
LFM2.5-VL-450M
$0.2 / $1.25
$0 / $0
191 t/s
N/A
3.64s
N/A
400K
128K
Pick GPT-5.4 nano 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-5.4 nano is clearly ahead on the provisional aggregate, 61 to 33. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 nano's sharpest advantage is in knowledge, where it averages 53.2 against 21.6. The single biggest benchmark swing on the page is GPQA, 82.8% to 25.7%.
GPT-5.4 nano is also the more expensive model on tokens at $0.20 input / $1.25 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-5.4 nano 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-5.4 nano gives you the larger context window at 400K, compared with 128K for LFM2.5-VL-450M.
GPT-5.4 nano is ahead on BenchLM's provisional leaderboard, 61 to 33. The biggest single separator in this matchup is GPQA, where the scores are 82.8% and 25.7%.
GPT-5.4 nano has the edge for knowledge tasks in this comparison, averaging 53.2 versus 21.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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