Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.5
63
Sakana Fugu Ultra
100
Verified leaderboard positions: Kimi K2.5 #18 · Sakana Fugu Ultra unranked
Pick Sakana Fugu Ultra if you want the stronger benchmark profile. Kimi K2.5 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.
Agentic
+27.5 difference
Coding
+19.3 difference
Knowledge
+30.4 difference
Kimi K2.5
Sakana Fugu Ultra
$0.6 / $3
$5 / $30
45 t/s
N/A
2.38s
N/A
256K
1M
Pick Sakana Fugu Ultra if you want the stronger benchmark profile. Kimi K2.5 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 63. 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 65.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 50.8% to 82.1%.
Sakana Fugu Ultra is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $0.60 input / $3.00 output per 1M tokens for Kimi K2.5. That is roughly 10.0x on output cost alone. Sakana Fugu Ultra is the reasoning model in the pair, while Kimi K2.5 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 256K for Kimi K2.5.
Sakana Fugu Ultra is ahead on BenchLM's provisional leaderboard, 100 to 63. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 50.8% and 82.1%.
Sakana Fugu Ultra has the edge for knowledge tasks in this comparison, averaging 95.5 versus 65.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Sakana Fugu Ultra has the edge for coding in this comparison, averaging 83.5 versus 64.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Sakana Fugu Ultra has the edge for agentic tasks in this comparison, averaging 82.1 versus 54.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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