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LFM2.5-230M vs MAI-Thinking-1

Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.

LFM2.5-230M

17

VS

MAI-Thinking-1

65

0 categoriesvs2 categories

Verified leaderboard positions: LFM2.5-230M unranked · MAI-Thinking-1 #26

Pick MAI-Thinking-1 if you want the stronger benchmark profile. LFM2.5-230M only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.

Category Radar

Head-to-Head by Category

Category Breakdown

Knowledge

MAI-Thinking-1
20.3vs69.9

+49.6 difference

Inst. Following

MAI-Thinking-1
71.7vs85

+13.3 difference

Operational Comparison

LFM2.5-230M

MAI-Thinking-1

Price (per 1M tokens)

$0 / $0

N/A

Speed

N/A

N/A

Latency (first answer)

N/A

N/A

Context Window

32K

256K

Quick Verdict

Pick MAI-Thinking-1 if you want the stronger benchmark profile. LFM2.5-230M only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.

MAI-Thinking-1 is clearly ahead on the provisional aggregate, 65 to 17. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

MAI-Thinking-1's sharpest advantage is in knowledge, where it averages 69.9 against 20.3. The single biggest benchmark swing on the page is MMLU-Pro, 20.3% to 85%.

MAI-Thinking-1 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. MAI-Thinking-1 gives you the larger context window at 256K, compared with 32K for LFM2.5-230M.

Benchmark Deep Dive

Frequently Asked Questions (3)

Which is better, LFM2.5-230M or MAI-Thinking-1?

MAI-Thinking-1 is ahead on BenchLM's provisional leaderboard, 65 to 17. The biggest single separator in this matchup is MMLU-Pro, where the scores are 20.3% and 85%.

Which is better for knowledge tasks, LFM2.5-230M or MAI-Thinking-1?

MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 69.9 versus 20.3. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.

Which is better for instruction following, LFM2.5-230M or MAI-Thinking-1?

MAI-Thinking-1 has the edge for instruction following in this comparison, averaging 85 versus 71.7. LFM2.5-230M stays close enough that the answer can still flip depending on your workload.

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Last updated: June 29, 2026

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