Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
LFM2.5-8B-A1B
50
Qwen3.5 397B
63
Verified leaderboard positions: LFM2.5-8B-A1B unranked · Qwen3.5 397B #19
Pick Qwen3.5 397B if you want the stronger benchmark profile. LFM2.5-8B-A1B only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
Inst. Following
+13.1 difference
LFM2.5-8B-A1B
Qwen3.5 397B
$0 / $0
$0.6 / $3.6
N/A
96 t/s
N/A
2.44s
128K
128K
Pick Qwen3.5 397B if you want the stronger benchmark profile. LFM2.5-8B-A1B only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
Qwen3.5 397B is clearly ahead on the provisional aggregate, 63 to 50. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5 397B's sharpest advantage is in instruction following, where it averages 92.6 against 79.5. The single biggest benchmark swing on the page is IFEval, 91.8% to 92.6%.
Qwen3.5 397B is also the more expensive model on tokens at $0.60 input / $3.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for LFM2.5-8B-A1B. That is roughly Infinityx on output cost alone. LFM2.5-8B-A1B is the reasoning model in the pair, while Qwen3.5 397B 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.
Qwen3.5 397B is ahead on BenchLM's provisional leaderboard, 63 to 50. The biggest single separator in this matchup is IFEval, where the scores are 91.8% and 92.6%.
Qwen3.5 397B has the edge for instruction following in this comparison, averaging 92.6 versus 79.5. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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