Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Flash Base
31
LFM2.5-230M
17
Pick DeepSeek V4 Flash Base if you want the stronger benchmark profile. LFM2.5-230M only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Knowledge
+31.9 difference
DeepSeek V4 Flash Base
LFM2.5-230M
$null / $null
$0 / $0
N/A
N/A
N/A
N/A
1M
32K
Pick DeepSeek V4 Flash Base if you want the stronger benchmark profile. LFM2.5-230M only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
DeepSeek V4 Flash Base is clearly ahead on the provisional aggregate, 31 to 17. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V4 Flash Base's sharpest advantage is in knowledge, where it averages 52.2 against 20.3. The single biggest benchmark swing on the page is MMLU-Pro, 68.3% to 20.3%.
DeepSeek V4 Flash Base gives you the larger context window at 1M, compared with 32K for LFM2.5-230M.
DeepSeek V4 Flash Base is ahead on BenchLM's provisional leaderboard, 31 to 17. The biggest single separator in this matchup is MMLU-Pro, where the scores are 68.3% and 20.3%.
DeepSeek V4 Flash Base has the edge for knowledge tasks in this comparison, averaging 52.2 versus 20.3. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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