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Model comparison

Celeris-1 vs Sakana Fugu

Data verified

Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

No sourced benchmark result is currently shared by both models. This page therefore compares only the available metadata, pricing, and runtime rows; it does not name a quality winner.
Celeris
N/A
No comparison
Sakana AI
N/A
0 category wins1 category wins

Evidence parity. Celeris-1 and Sakana Fugu share 0 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Celeris-1; 11 to Sakana Fugu.

Updated July 24, 2026
Shared results
0
Celeris-1 only
1
Sakana Fugu only
11
Comparable categories
1 / 8

Treat this as a split decision. Celeris-1 makes more sense if you would rather avoid the extra latency and token burn of a reasoning model; Sakana Fugu is the better fit if knowledge is the priority or you need the larger 1M context window.

Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Celeris-1 and Sakana Fugu finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

Sakana Fugu is the reasoning model in the pair, while Celeris-1 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 gives you the larger context window at 1M, compared with 8K for Celeris-1.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricCeleris-1Sakana FuguComparison
Input / output priceUSD per 1M tokensCeleris-1$2 input / $6 outputSakana FuguNot availableA complete price comparison is not available.
Generation speedtokens per secondCeleris-1Not availableSakana FuguNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenCeleris-1Not availableSakana FuguNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensCeleris-18KSakana Fugu1MSakana Fugu lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkCeleris-1Sakana FuguResult
Terminal-Bench 2.0Source 80.2%Not comparable
Coding
BenchmarkCeleris-1Sakana FuguResult
SWE-bench ProSource 59%Not comparable
Terminal-Bench 2.0Source 80.2%Not comparable
LiveCodeBench v6Source 92.9%Not comparable
LiveCodeBench ProSource 87.8%Not comparable
SciCodeSource 60.1%Not comparable
Reasoning
BenchmarkCeleris-1Sakana FuguResult
MRCRv2Source 86.6%Not comparable
KnowledgeSakana Fugu wins
BenchmarkCeleris-1Sakana FuguResult
MMLU-ProSource 75.9%Not comparable
GPQASource 95.5%Not comparable
GPQA-DSource 95.5%Not comparable
HLE w/o toolsSource 47.2%Not comparable
Multimodal
BenchmarkCeleris-1Sakana FuguResult
CharXivSource 85.1%Not comparable
Frequently Asked Questions (2)

Which is better, Celeris-1 or Sakana Fugu?

Celeris-1 and Sakana Fugu are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for knowledge tasks, Celeris-1 or Sakana Fugu?

Sakana Fugu has the edge for knowledge tasks in this comparison, averaging 95.5 versus 75.9. Celeris-1 stays close enough that the answer can still flip depending on your workload.

Related Comparisons

Last updated: July 24, 2026

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