Model comparison
GPT-5.6 Sol vs Sakana Fugu-Ultra
Head-to-head evidence from 5 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.6 Sol #3 (Supported); Sakana Fugu-Ultra unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Sol and Sakana Fugu-Ultra share 5 comparable benchmark results. 4 of 8 categories are comparable. 41 results are unique to GPT-5.6 Sol; 6 to Sakana Fugu-Ultra.
Updated July 23, 2026- Shared results
- 5
- GPT-5.6 Sol only
- 41
- Sakana Fugu-Ultra only
- 6
- Comparable categories
- 4 / 8
Treat this as a split decision. GPT-5.6 Sol makes more sense if agentic is the priority; Sakana Fugu-Ultra is the better fit if multimodal & grounded is the priority.
Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 3 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.6 Sol 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 | GPT-5.6 Sol | Δ | Sakana Fugu-Ultra |
|---|---|---|---|
| Agentic | GPT-5.6 Sol92.0 | Margin← 9.9 | Sakana Fugu-Ultra82.1 |
| Multimodal | GPT-5.6 Sol83.0 | Margin→ 3.6 | Sakana Fugu-Ultra86.6 |
| Knowledge | GPT-5.6 Sol94.6 | Margin→ 0.9 | Sakana Fugu-Ultra95.5 |
| Coding | GPT-5.6 Sol64.6 | Margin← 0.1 | Sakana Fugu-Ultra64.5 |
| Reasoning | GPT-5.6 SolNot measured | MarginNo overlap | Sakana Fugu-Ultra93.6 |
| Math | GPT-5.6 Sol87.5 | MarginNo overlap | Sakana Fugu-UltraNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 91.9%B 82.1%Winner: GPT-5.6 SolΔ 9.8Terminal-Bench 2.0: GPT-5.6 Sol scored 91.9%; Sakana Fugu-Ultra scored 82.1%. GPT-5.6 Sol wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 64.6%B 73.7%Winner: Sakana Fugu-UltraΔ 9.1SWE-bench Pro: GPT-5.6 Sol scored 64.6%; Sakana Fugu-Ultra scored 73.7%. Sakana Fugu-Ultra wins this benchmark. - Source ↗
GPQA
KnowledgeA 94.6%B 95.5%Winner: Sakana Fugu-UltraΔ 0.9GPQA: GPT-5.6 Sol scored 94.6%; 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 | GPT-5.6 Sol | Sakana Fugu-Ultra | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Sol$5 input / $30 output | Sakana Fugu-UltraNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.6 SolNot available | Sakana Fugu-UltraNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 SolNot available | Sakana Fugu-UltraNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Sol1M | Sakana Fugu-Ultra1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGPT-5.6 Sol wins17 benchmarks
| Benchmark | GPT-5.6 Sol | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 91.9% | 82.1% | GPT-5.6 Sol leads |
| BrowseCompSource | 92.2% | — | Not comparable |
| OSWorld 2.0Source | 62.6% | — | Not comparable |
| CyberGymSource | 84.5% | — | Not comparable |
| ExploitGymSource | 33.7% | — | Not comparable |
| ToolathlonSource | 58% | — | Not comparable |
| AA Agentic IndexSource | 54.0% | — | Not comparable |
| τ²-bench resultsSource | 85.1% | — | Not comparable |
| GDPval-AASource | 61.8% | — | Not comparable |
| GDPval-AASource | 1736 | — | Not comparable |
| AA BriefcaseSource | 1501 | — | Not comparable |
| AA ITBenchSource | 56.2% | — | Not comparable |
| AA Tau3 BankingSource | 33.0% | — | Not comparable |
| AA AutomationBenchSource | 51.2% | — | Not comparable |
| AA Harvey LABSource | 87.2% | — | Not comparable |
| terminalBenchHardSource | 65.9% | — | Not comparable |
| aaTerminalBench21Source | 88% | — | Not comparable |
CodingGPT-5.6 Sol wins11 benchmarks
| Benchmark | GPT-5.6 Sol | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| SWE-bench ProSource | 64.6% | 73.7% | Sakana Fugu-Ultra leads |
| Terminal-Bench 2.0Source | 91.9% | 82.1% | GPT-5.6 Sol leads |
| deepSweSource | 72.7% | — | Not comparable |
| FrontierCode 1.1 ExtendedSource | 60.6% | — | Not comparable |
| cursorBench32Source | 67.2% | — | Not comparable |
| VulcanBench v3Source | 87.0% | — | Not comparable |
| AA Coding IndexSource | 77.4% | — | Not comparable |
| AA-SciCodeSource | 56.1% | — | Not comparable |
| LiveCodeBench v6Source | — | 93.2% | Not comparable |
| LiveCodeBench ProSource | — | 90.8% | Not comparable |
| SciCodeSource | — | 58.7% | Not comparable |
Reasoning5 benchmarks
KnowledgeSakana Fugu-Ultra wins11 benchmarks
| Benchmark | GPT-5.6 Sol | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| GPQASource | 94.6% | 95.5% | Sakana Fugu-Ultra leads |
| GPQA-DSource | 94.6% | 95.5% | Sakana Fugu-Ultra leads |
| HealthBench ProfessionalSource | 60.5% | — | Not comparable |
| HealthBench HardSource | 33.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 58.9% | — | Not comparable |
| AA-GPQA DiamondSource | 94.1% | — | Not comparable |
| AA-HLESource | 47.2% | — | Not comparable |
| AA-Omniscience IndexSource | 21.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 58.5% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 88.8% | — | Not comparable |
| HLE w/o toolsSource | — | 50% | Not comparable |
Math3 benchmarks
MultimodalSakana Fugu-Ultra wins4 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.6 Sol | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| AA-IFBenchSource | 72.7% | — | Not comparable |
Frequently Asked Questions (5)
Which is better, GPT-5.6 Sol or Sakana Fugu-Ultra?
GPT-5.6 Sol 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, GPT-5.6 Sol or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for knowledge tasks in this comparison, averaging 95.5 versus 94.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.6 Sol or Sakana Fugu-Ultra?
GPT-5.6 Sol has the edge for coding in this comparison, averaging 64.6 versus 64.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.6 Sol or Sakana Fugu-Ultra?
GPT-5.6 Sol has the edge for agentic tasks in this comparison, averaging 92 versus 82.1. 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, GPT-5.6 Sol or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for multimodal and grounded tasks in this comparison, averaging 86.6 versus 83. GPT-5.6 Sol stays close enough that the answer can still flip depending on your workload.
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