Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Fable 5
95
LFM2.5-230M
17
Verified leaderboard positions: Claude Fable 5 #2 · LFM2.5-230M unranked
Pick Claude Fable 5 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
+54.5 difference
Claude Fable 5
LFM2.5-230M
$10 / $50
$0 / $0
N/A
N/A
N/A
N/A
1M+
32K
Pick Claude Fable 5 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.
Claude Fable 5 is clearly ahead on the provisional aggregate, 95 to 17. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Fable 5's sharpest advantage is in knowledge, where it averages 74.8 against 20.3.
Claude Fable 5 is also the more expensive model on tokens at $10.00 input / $50.00 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. Claude Fable 5 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. Claude Fable 5 gives you the larger context window at 1M+, compared with 32K for LFM2.5-230M.
Claude Fable 5 is ahead on BenchLM's provisional leaderboard, 95 to 17.
Claude Fable 5 has the edge for knowledge tasks in this comparison, averaging 74.8 versus 20.3. LFM2.5-230M stays close enough that the answer can still flip depending on your workload.
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