Model comparison
Claude Opus 4.7 (Adaptive) vs Sakana Fugu-Ultra
Head-to-head evidence from 7 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); Sakana Fugu-Ultra unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.7 (Adaptive) and Sakana Fugu-Ultra share 7 comparable benchmark results. 5 of 8 categories are comparable. 31 results are unique to Claude Opus 4.7 (Adaptive); 4 to Sakana Fugu-Ultra.
Updated July 23, 2026- Shared results
- 7
- Claude Opus 4.7 (Adaptive) only
- 31
- Sakana Fugu-Ultra only
- 4
- Comparable categories
- 5 / 8
Treat this as a split decision. Claude Opus 4.7 (Adaptive) makes more sense if coding is the priority; Sakana Fugu-Ultra is the better fit if knowledge is the priority.
Confidence note. This is a partial-evidence comparison with 7 shared benchmark results across 4 evidence categories; 5 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Claude Opus 4.7 (Adaptive) 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.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Claude Opus 4.7 (Adaptive) | Δ | Sakana Fugu-Ultra |
|---|---|---|---|
| Knowledge | Claude Opus 4.7 (Adaptive)60.0 | Margin→ 35.5 | Sakana Fugu-Ultra95.5 |
| Multimodal | Claude Opus 4.7 (Adaptive)65.1 | Margin→ 21.5 | Sakana Fugu-Ultra86.6 |
| Reasoning | Claude Opus 4.7 (Adaptive)75.8 | Margin→ 17.8 | Sakana Fugu-Ultra93.6 |
| Coding | Claude Opus 4.7 (Adaptive)78.6 | Margin← 14.1 | Sakana Fugu-Ultra64.5 |
| Agentic | Claude Opus 4.7 (Adaptive)75.1 | Margin→ 7.0 | Sakana Fugu-Ultra82.1 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 69.4%B 82.1%Winner: Sakana Fugu-UltraΔ 12.7Terminal-Bench 2.0: Claude Opus 4.7 (Adaptive) scored 69.4%; Sakana Fugu-Ultra scored 82.1%. Sakana Fugu-Ultra wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 64.3%B 73.7%Winner: Sakana Fugu-UltraΔ 9.4SWE-bench Pro: Claude Opus 4.7 (Adaptive) scored 64.3%; Sakana Fugu-Ultra scored 73.7%. Sakana Fugu-Ultra wins this benchmark. - Source ↗
CharXiv
MultimodalA 91%B 86.6%Winner: Claude Opus 4.7 (Adaptive)Δ 4.4CharXiv: Claude Opus 4.7 (Adaptive) scored 91%; Sakana Fugu-Ultra scored 86.6%. Claude Opus 4.7 (Adaptive) wins this benchmark. - Source ↗
GPQA
KnowledgeA 94.2%B 95.5%Winner: Sakana Fugu-UltraΔ 1.3GPQA: Claude Opus 4.7 (Adaptive) scored 94.2%; Sakana Fugu-Ultra scored 95.5%. Sakana Fugu-Ultra wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.7 (Adaptive) | Sakana Fugu-Ultra | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7 (Adaptive)$5 input / $25 output | Sakana Fugu-UltraNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Claude Opus 4.7 (Adaptive)Not available | Sakana Fugu-UltraNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7 (Adaptive)Not available | Sakana Fugu-UltraNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.7 (Adaptive)1M | Sakana Fugu-Ultra1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticSakana Fugu-Ultra wins12 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 69.4% | 82.1% | Sakana Fugu-Ultra leads |
| BrowseCompSource | 79.3% | — | Not comparable |
| MCP AtlasSource | 77.3% | — | Not comparable |
| OSWorld-VerifiedSource | 78% | — | Not comparable |
| CyberGymSource | 73.1% | — | Not comparable |
| AA Agentic IndexSource | 44.4% | — | Not comparable |
| τ²-bench resultsSource | 88.6% | — | Not comparable |
| GDPval-AASource | 49.8% | — | Not comparable |
| GDPval-AASource | 1495 | — | Not comparable |
| OSWorld 2.0Source | 18.2% | — | Not comparable |
| JobBenchSource | 45.9% | — | Not comparable |
| AA ITBenchSource | 46.7% | — | Not comparable |
CodingClaude Opus 4.7 (Adaptive) wins8 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 87.6% | — | Not comparable |
| SWE-bench ProSource | 64.3% | 73.7% | Sakana Fugu-Ultra leads |
| Terminal-Bench 2.0Source | 69.4% | 82.1% | Sakana Fugu-Ultra leads |
| AA Coding IndexSource | 73.6% | — | Not comparable |
| AA-SciCodeSource | 54.5% | — | Not comparable |
| LiveCodeBench v6Source | — | 93.2% | Not comparable |
| LiveCodeBench ProSource | — | 90.8% | Not comparable |
| SciCodeSource | — | 58.7% | Not comparable |
ReasoningSakana Fugu-Ultra wins5 benchmarks
KnowledgeSakana Fugu-Ultra wins10 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| GPQASource | 94.2% | 95.5% | Sakana Fugu-Ultra leads |
| GPQA-DSource | 94.2% | 95.5% | Sakana Fugu-Ultra leads |
| HLESource | 54.7% | — | Not comparable |
| HLE w/o toolsSource | 46.9% | 50% | Sakana Fugu-Ultra leads |
| Artificial Analysis Intelligence IndexSource | 53.5% | — | Not comparable |
| AA-GPQA DiamondSource | 91.4% | — | Not comparable |
| AA-HLESource | 39.6% | — | Not comparable |
| AA-Omniscience IndexSource | 26.2% | — | Not comparable |
| AA-Omniscience AccuracySource | 45.8% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 36.2% | — | Not comparable |
Math1 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| FrontierMath (legacy)Source | 43.8% | — | Not comparable |
MultimodalSakana Fugu-Ultra wins5 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| AA-IFBenchSource | 58.6% | — | Not comparable |
Frequently Asked Questions (6)
Which is better, Claude Opus 4.7 (Adaptive) or Sakana Fugu-Ultra?
Claude Opus 4.7 (Adaptive) 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, Claude Opus 4.7 (Adaptive) or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for knowledge tasks in this comparison, averaging 95.5 versus 60. Inside this category, HLE w/o tools is the benchmark that creates the most daylight between them.
Which is better for coding, Claude Opus 4.7 (Adaptive) or Sakana Fugu-Ultra?
Claude Opus 4.7 (Adaptive) has the edge for coding in this comparison, averaging 78.6 versus 64.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for reasoning, Claude Opus 4.7 (Adaptive) or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for reasoning in this comparison, averaging 93.6 versus 75.8. Claude Opus 4.7 (Adaptive) stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, Claude Opus 4.7 (Adaptive) or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for agentic tasks in this comparison, averaging 82.1 versus 75.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, Claude Opus 4.7 (Adaptive) or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for multimodal and grounded tasks in this comparison, averaging 86.6 versus 65.1. Inside this category, CharXiv is the benchmark that creates the most daylight between them.
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