Model comparison
Qwen3.5-122B-A10B vs Sakana Fugu-Ultra
Head-to-head evidence from 3 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Qwen3.5-122B-A10B #47 (Supported); Sakana Fugu-Ultra unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Qwen3.5-122B-A10B and Sakana Fugu-Ultra share 3 comparable benchmark results. 5 of 8 categories are comparable. 28 results are unique to Qwen3.5-122B-A10B; 8 to Sakana Fugu-Ultra.
Updated July 23, 2026- Shared results
- 3
- Qwen3.5-122B-A10B only
- 28
- Sakana Fugu-Ultra only
- 8
- Comparable categories
- 5 / 8
Treat this as a split decision. Qwen3.5-122B-A10B makes more sense if coding is the priority; Sakana Fugu-Ultra is the better fit if reasoning is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 3 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
Qwen3.5-122B-A10B 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 gives you the larger context window at 1M, compared with 262K for Qwen3.5-122B-A10B.
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 | Qwen3.5-122B-A10B | Δ | Sakana Fugu-Ultra |
|---|---|---|---|
| Reasoning | Qwen3.5-122B-A10B60.2 | Margin→ 33.4 | Sakana Fugu-Ultra93.6 |
| Agentic | Qwen3.5-122B-A10B56.4 | Margin→ 25.7 | Sakana Fugu-Ultra82.1 |
| Knowledge | Qwen3.5-122B-A10B83.6 | Margin→ 11.9 | Sakana Fugu-Ultra95.5 |
| Multimodal | Qwen3.5-122B-A10B77.2 | Margin→ 9.4 | Sakana Fugu-Ultra86.6 |
| Coding | Qwen3.5-122B-A10B72.0 | Margin← 7.5 | Sakana Fugu-Ultra64.5 |
| Multilingual | Qwen3.5-122B-A10B82.2 | MarginNo overlap | Sakana Fugu-UltraNot measured |
| Inst. Following | Qwen3.5-122B-A10B93.4 | 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 49.4%B 82.1%Winner: Sakana Fugu-UltraΔ 32.7Terminal-Bench 2.0: Qwen3.5-122B-A10B scored 49.4%; Sakana Fugu-Ultra scored 82.1%. Sakana Fugu-Ultra wins this benchmark. - Source ↗
CharXiv
MultimodalA 77.2%B 86.6%Winner: Sakana Fugu-UltraΔ 9.4CharXiv: Qwen3.5-122B-A10B scored 77.2%; Sakana Fugu-Ultra scored 86.6%. Sakana Fugu-Ultra wins this benchmark. - Source ↗
GPQA
KnowledgeA 86.6%B 95.5%Winner: Sakana Fugu-UltraΔ 8.9GPQA: Qwen3.5-122B-A10B scored 86.6%; 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 | Qwen3.5-122B-A10B | Sakana Fugu-Ultra | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Qwen3.5-122B-A10B$0 input / $0 output | Sakana Fugu-UltraNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Qwen3.5-122B-A10BNot available | Sakana Fugu-UltraNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Qwen3.5-122B-A10BNot available | Sakana Fugu-UltraNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Qwen3.5-122B-A10B262K | Sakana Fugu-Ultra1M | Sakana Fugu-Ultra lists the larger context window. |
Benchmark Deep Dive
AgenticSakana Fugu-Ultra wins7 benchmarks
| Benchmark | Qwen3.5-122B-A10B | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 49.4% | 82.1% | Sakana Fugu-Ultra leads |
| BrowseCompSource | 63.8% | — | Not comparable |
| OSWorld-VerifiedSource | 58% | — | Not comparable |
| τ²-bench resultsSource | 93.6% | — | Not comparable |
| AA Agentic IndexSource | 20.7% | — | Not comparable |
| GDPval-AASource | 23.9% | — | Not comparable |
| GDPval-AASource | 978 | — | Not comparable |
CodingQwen3.5-122B-A10B wins8 benchmarks
| Benchmark | Qwen3.5-122B-A10B | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 72% | — | Not comparable |
| AA Coding IndexSource | 45.7% | — | Not comparable |
| AA-SciCodeSource | 42.0% | — | Not comparable |
| SWE-bench ProSource | — | 73.7% | Not comparable |
| Terminal-Bench 2.0Source | — | 82.1% | Not comparable |
| LiveCodeBench v6Source | — | 93.2% | Not comparable |
| LiveCodeBench ProSource | — | 90.8% | Not comparable |
| SciCodeSource | — | 58.7% | Not comparable |
ReasoningSakana Fugu-Ultra wins4 benchmarks
KnowledgeSakana Fugu-Ultra wins11 benchmarks
| Benchmark | Qwen3.5-122B-A10B | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| MMLU-ProSource | 86.7% | — | Not comparable |
| SuperGPQASource | 67.1% | — | Not comparable |
| GPQASource | 86.6% | 95.5% | Sakana Fugu-Ultra leads |
| Artificial Analysis Intelligence IndexSource | 32.3% | — | Not comparable |
| AA-GPQA DiamondSource | 85.7% | — | Not comparable |
| AA-HLESource | 23.4% | — | Not comparable |
| AA-Omniscience IndexSource | -39.6% | — | Not comparable |
| AA-Omniscience AccuracySource | 24.7% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 85.5% | — | Not comparable |
| GPQA-DSource | — | 95.5% | Not comparable |
| HLE w/o toolsSource | — | 50% | Not comparable |
Multilingual1 benchmarks
| Benchmark | Qwen3.5-122B-A10B | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| MMLU-ProXSource | 82.2% | — | Not comparable |
MultimodalSakana Fugu-Ultra wins6 benchmarks
Frequently Asked Questions (6)
Which is better, Qwen3.5-122B-A10B or Sakana Fugu-Ultra?
Qwen3.5-122B-A10B 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, Qwen3.5-122B-A10B or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for knowledge tasks in this comparison, averaging 95.5 versus 83.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, Qwen3.5-122B-A10B or Sakana Fugu-Ultra?
Qwen3.5-122B-A10B has the edge for coding in this comparison, averaging 72 versus 64.5. Sakana Fugu-Ultra stays close enough that the answer can still flip depending on your workload.
Which is better for reasoning, Qwen3.5-122B-A10B or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for reasoning in this comparison, averaging 93.6 versus 60.2. Qwen3.5-122B-A10B stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, Qwen3.5-122B-A10B or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for agentic tasks in this comparison, averaging 82.1 versus 56.4. 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, Qwen3.5-122B-A10B or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for multimodal and grounded tasks in this comparison, averaging 86.6 versus 77.2. Inside this category, CharXiv is the benchmark that creates the most daylight between them.
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