Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1 mini
55
LFM2.5-VL-450M
33
Pick GPT-4.1 mini if you want the stronger benchmark profile. LFM2.5-VL-450M only becomes the better choice if you want the cheaper token bill.
Knowledge
+42.6 difference
Inst. Following
+27.3 difference
GPT-4.1 mini
LFM2.5-VL-450M
$0.4 / $1.6
$0 / $0
80 t/s
N/A
0.76s
N/A
1M
128K
Pick GPT-4.1 mini if you want the stronger benchmark profile. LFM2.5-VL-450M only becomes the better choice if you want the cheaper token bill.
GPT-4.1 mini is clearly ahead on the provisional aggregate, 55 to 33. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1 mini's sharpest advantage is in knowledge, where it averages 64.2 against 21.6. The single biggest benchmark swing on the page is GPQA, 64.2% to 25.7%.
GPT-4.1 mini is also the more expensive model on tokens at $0.40 input / $1.60 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-4.1 mini gives you the larger context window at 1M, compared with 128K for LFM2.5-VL-450M.
GPT-4.1 mini is ahead on BenchLM's provisional leaderboard, 55 to 33. The biggest single separator in this matchup is GPQA, where the scores are 64.2% and 25.7%.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 64.2 versus 21.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for instruction following in this comparison, averaging 88.5 versus 61.2. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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