Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude 4 Sonnet
50
Sakana Fugu Ultra
100
Pick Sakana Fugu Ultra if you want the stronger benchmark profile. Claude 4 Sonnet only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+10.8 difference
Claude 4 Sonnet
Sakana Fugu Ultra
$3 / $15
$5 / $30
40 t/s
N/A
1.33s
N/A
200K
1M
Pick Sakana Fugu Ultra if you want the stronger benchmark profile. Claude 4 Sonnet only becomes the better choice if you want the cheaper token bill or 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 50. 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 coding, where it averages 83.5 against 72.7.
Sakana Fugu Ultra is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $3.00 input / $15.00 output per 1M tokens for Claude 4 Sonnet. That is roughly 2.0x on output cost alone. Sakana Fugu Ultra is the reasoning model in the pair, while Claude 4 Sonnet 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 gives you the larger context window at 1M, compared with 200K for Claude 4 Sonnet.
Sakana Fugu Ultra is ahead on BenchLM's provisional leaderboard, 100 to 50.
Sakana Fugu Ultra has the edge for coding in this comparison, averaging 83.5 versus 72.7. Claude 4 Sonnet stays close enough that the answer can still flip depending on your workload.
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