Model comparison
Qwen3.7 Max vs Sakana Fugu
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: Qwen3.7 Max #10 (Supported); Sakana Fugu unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Qwen3.7 Max and Sakana Fugu share 7 comparable benchmark results. 4 of 8 categories are comparable. 51 results are unique to Qwen3.7 Max; 4 to Sakana Fugu.
Updated July 23, 2026- Shared results
- 7
- Qwen3.7 Max only
- 51
- Sakana Fugu only
- 4
- Comparable categories
- 4 / 8
Treat this as a split decision. Qwen3.7 Max makes more sense if coding is the priority; Sakana Fugu 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; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.7 Max 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.
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 | Qwen3.7 Max | Δ | Sakana Fugu |
|---|---|---|---|
| Knowledge | Qwen3.7 Max64.2 | Margin→ 31.3 | Sakana Fugu95.5 |
| Coding | Qwen3.7 Max77.9 | Margin← 18.2 | Sakana Fugu59.7 |
| Agentic | Qwen3.7 Max69.7 | Margin→ 10.5 | Sakana Fugu80.2 |
| Reasoning | Qwen3.7 Max90.4 | Margin← 3.8 | Sakana Fugu86.6 |
| Math | Qwen3.7 Max97.1 | MarginNo overlap | Sakana FuguNot measured |
| Multilingual | Qwen3.7 Max87.0 | MarginNo overlap | Sakana FuguNot measured |
| Multimodal | Qwen3.7 MaxNot measured | MarginNo overlap | Sakana Fugu85.1 |
| Inst. Following | Qwen3.7 Max84.4 | MarginNo overlap | Sakana FuguNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 69.7%B 80.2%Winner: Sakana FuguΔ 10.5Terminal-Bench 2.0: Qwen3.7 Max scored 69.7%; Sakana Fugu scored 80.2%. Sakana Fugu wins this benchmark. - Source ↗
SciCode
CodingA 53.5%B 60.1%Winner: Sakana FuguΔ 6.6SciCode: Qwen3.7 Max scored 53.5%; Sakana Fugu scored 60.1%. Sakana Fugu wins this benchmark. - Source ↗
MRCRv2
ReasoningA 90.4%B 86.6%Winner: Qwen3.7 MaxΔ 3.8MRCRv2: Qwen3.7 Max scored 90.4%; Sakana Fugu scored 86.6%. Qwen3.7 Max wins this benchmark. - Source ↗
GPQA
KnowledgeA 92.4%B 95.5%Winner: Sakana FuguΔ 3.1GPQA: Qwen3.7 Max scored 92.4%; Sakana Fugu scored 95.5%. Sakana Fugu wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 60.6%B 59%Winner: Qwen3.7 MaxΔ 1.6SWE-bench Pro: Qwen3.7 Max scored 60.6%; Sakana Fugu scored 59%. Qwen3.7 Max wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Qwen3.7 Max | Sakana Fugu | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Qwen3.7 MaxNot available | Sakana FuguNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Qwen3.7 MaxNot available | Sakana FuguNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Qwen3.7 MaxNot available | Sakana FuguNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Qwen3.7 Max1M | Sakana Fugu1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticSakana Fugu wins21 benchmarks
| Benchmark | Qwen3.7 Max | Sakana Fugu | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 69.7% | 80.2% | Sakana Fugu leads |
| QwenClawBenchSource | 64.3% | — | Not comparable |
| QwenWebBenchSource | 1568 | — | Not comparable |
| Claw-EvalSource | 65.2% | — | Not comparable |
| BFCL v4Source | 75.0% | — | Not comparable |
| MCP AtlasSource | 76.4% | — | Not comparable |
| VITA-BenchSource | 47.9% | — | Not comparable |
| HLE w/ toolsSource | 53.5% | — | Not comparable |
| AA Agentic IndexSource | 30.6% | — | Not comparable |
| τ²-bench resultsSource | 94.7% | — | Not comparable |
| GDPval-AASource | 38.7% | — | Not comparable |
| GDPval-AASource | 1273 | — | Not comparable |
| Gert LabsSource | 64.27% | — | Not comparable |
| ResearchClawBenchSource | 18.7% | — | Not comparable |
| AA BriefcaseSource | 908 | — | Not comparable |
| AA AutomationBenchSource | 25.6% | — | Not comparable |
| AA EnterpriseOps-GymSource | 45.0% | — | Not comparable |
| AA ITBenchSource | 42.5% | — | Not comparable |
| terminalBenchHardSource | 50.8% | — | Not comparable |
| aaTerminalBench21Source | 74.5% | — | Not comparable |
| AA Harvey LABSource | 83.4% | — | Not comparable |
CodingQwen3.7 Max wins11 benchmarks
| Benchmark | Qwen3.7 Max | Sakana Fugu | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.4% | — | Not comparable |
| SWE-bench ProSource | 60.6% | 59% | Qwen3.7 Max leads |
| SWE MultilingualSource | 78.3% | — | Not comparable |
| NL2RepoSource | 47.2% | — | Not comparable |
| SciCodeSource | 53.5% | 60.1% | Sakana Fugu leads |
| LiveCodeBenchSource | 91.6% | — | Not comparable |
| Terminal-Bench 2.0Source | 69.7% | 80.2% | Sakana Fugu leads |
| AA Coding IndexSource | 66.0% | — | Not comparable |
| AA-SciCodeSource | 48.8% | — | Not comparable |
| LiveCodeBench v6Source | — | 92.9% | Not comparable |
| LiveCodeBench ProSource | — | 87.8% | Not comparable |
ReasoningQwen3.7 Max wins3 benchmarks
KnowledgeSakana Fugu wins14 benchmarks
| Benchmark | Qwen3.7 Max | Sakana Fugu | Result |
|---|---|---|---|
| GPQASource | 92.4% | 95.5% | Sakana Fugu leads |
| GPQA-DSource | 92.4% | 95.5% | Sakana Fugu leads |
| HLESource | 41.4% | — | Not comparable |
| MMLU-ProSource | 89.6% | — | Not comparable |
| MMLU-ReduxSource | 95% | — | Not comparable |
| SuperGPQASource | 73.6% | — | Not comparable |
| MMMLUSource | 90.3% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 46.0% | — | Not comparable |
| AA-GPQA DiamondSource | 92.3% | — | Not comparable |
| AA-HLESource | 38.1% | — | Not comparable |
| AA-Omniscience IndexSource | 14.1% | — | Not comparable |
| AA-Omniscience AccuracySource | 30.1% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 22.9% | — | Not comparable |
| HLE w/o toolsSource | — | 47.2% | Not comparable |
Math3 benchmarks
Multilingual5 benchmarks
Multimodal2 benchmarks
Frequently Asked Questions (5)
Which is better, Qwen3.7 Max or Sakana Fugu?
Qwen3.7 Max 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, Qwen3.7 Max or Sakana Fugu?
Sakana Fugu has the edge for knowledge tasks in this comparison, averaging 95.5 versus 64.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, Qwen3.7 Max or Sakana Fugu?
Qwen3.7 Max has the edge for coding in this comparison, averaging 77.9 versus 59.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for reasoning, Qwen3.7 Max or Sakana Fugu?
Qwen3.7 Max has the edge for reasoning in this comparison, averaging 90.4 versus 86.6. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Qwen3.7 Max or Sakana Fugu?
Sakana Fugu has the edge for agentic tasks in this comparison, averaging 80.2 versus 69.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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