Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro Base
43
Sakana Fugu Ultra
100
Pick Sakana Fugu Ultra if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+32.1 difference
DeepSeek V4 Pro Base
Sakana Fugu Ultra
$null / $null
$5 / $30
N/A
N/A
N/A
N/A
1M
1M
Pick Sakana Fugu Ultra if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Sakana Fugu Ultra is clearly ahead on the provisional aggregate, 100 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Sakana Fugu Ultra's sharpest advantage is in knowledge, where it averages 95.5 against 63.4.
Sakana Fugu Ultra is the reasoning model in the pair, while DeepSeek V4 Pro 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.
Sakana Fugu Ultra is ahead on BenchLM's provisional leaderboard, 100 to 43.
Sakana Fugu Ultra has the edge for knowledge tasks in this comparison, averaging 95.5 versus 63.4. DeepSeek V4 Pro Base stays close enough that the answer can still flip depending on your workload.
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