Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Grok 4.3
72
LFM2.5-230M
17
Pick Grok 4.3 if you want the stronger benchmark profile. LFM2.5-230M 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
+33.6 difference
Inst. Following
+9.6 difference
Grok 4.3
LFM2.5-230M
$1.25 / $2.5
$0 / $0
209 t/s
N/A
12.36s
N/A
1M
32K
Pick Grok 4.3 if you want the stronger benchmark profile. LFM2.5-230M 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.
Grok 4.3 is clearly ahead on the provisional aggregate, 72 to 17. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Grok 4.3's sharpest advantage is in knowledge, where it averages 53.9 against 20.3.
Grok 4.3 is also the more expensive model on tokens at $1.25 input / $2.50 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for LFM2.5-230M. That is roughly Infinityx on output cost alone. Grok 4.3 is the reasoning model in the pair, while LFM2.5-230M 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. Grok 4.3 gives you the larger context window at 1M, compared with 32K for LFM2.5-230M.
Grok 4.3 is ahead on BenchLM's provisional leaderboard, 72 to 17.
Grok 4.3 has the edge for knowledge tasks in this comparison, averaging 53.9 versus 20.3. LFM2.5-230M stays close enough that the answer can still flip depending on your workload.
Grok 4.3 has the edge for instruction following in this comparison, averaging 81.3 versus 71.7. LFM2.5-230M stays close enough that the answer can still flip depending on your workload.
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