Model comparison
Celeris-1 vs Sakana Fugu-Ultra
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Evidence parity. Celeris-1 and Sakana Fugu-Ultra share 0 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Celeris-1; 11 to Sakana Fugu-Ultra.
Updated July 24, 2026- Shared results
- 0
- Celeris-1 only
- 1
- Sakana Fugu-Ultra 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-Ultra 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-Ultra 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-Ultra 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-Ultra 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.
| Metric | Celeris-1 | Sakana Fugu-Ultra | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | Sakana Fugu-UltraNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Celeris-1Not available | Sakana Fugu-UltraNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | Sakana Fugu-UltraNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | Sakana Fugu-Ultra1M | Sakana Fugu-Ultra lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | Celeris-1 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 82.1% | Not comparable |
Coding5 benchmarks
Reasoning1 benchmarks
| Benchmark | Celeris-1 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| MRCRv2Source | — | 93.6% | Not comparable |
KnowledgeSakana Fugu-Ultra wins4 benchmarks
Multimodal1 benchmarks
| Benchmark | Celeris-1 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| CharXivSource | — | 86.6% | Not comparable |
Frequently Asked Questions (2)
Which is better, Celeris-1 or Sakana Fugu-Ultra?
Celeris-1 and Sakana Fugu-Ultra 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-Ultra?
Sakana Fugu-Ultra 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.
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