Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Flash Base
31
Interfaze Beta
76
Pick Interfaze Beta if you want the stronger benchmark profile. DeepSeek V4 Flash Base only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+37.7 difference
DeepSeek V4 Flash Base
Interfaze Beta
$null / $null
$1.5 / $3.5
N/A
N/A
N/A
N/A
1M
1M
Pick Interfaze Beta if you want the stronger benchmark profile. DeepSeek V4 Flash Base only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Interfaze Beta is clearly ahead on the provisional aggregate, 76 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Interfaze Beta's sharpest advantage is in knowledge, where it averages 89.9 against 52.2.
Interfaze Beta is the reasoning model in the pair, while DeepSeek V4 Flash Base 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.
Interfaze Beta is ahead on BenchLM's provisional leaderboard, 76 to 31.
Interfaze Beta has the edge for knowledge tasks in this comparison, averaging 89.9 versus 52.2. Inside this category, MMMLU is the benchmark that creates the most daylight between them.
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