Model comparison
MAI-Thinking-1 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.
Evidence parity. MAI-Thinking-1 and Sakana Fugu-Ultra share 5 comparable benchmark results. 3 of 8 categories are comparable. 8 results are unique to MAI-Thinking-1; 6 to Sakana Fugu-Ultra.
Updated July 23, 2026- Shared results
- 5
- MAI-Thinking-1 only
- 8
- Sakana Fugu-Ultra only
- 6
- Comparable categories
- 3 / 8
Treat this as a split decision. MAI-Thinking-1 makes more sense if coding is the priority; Sakana Fugu-Ultra is the better fit if agentic is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 3 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
MAI-Thinking-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 gives you the larger context window at 1M, compared with 256K for MAI-Thinking-1.
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 | MAI-Thinking-1 | Δ | Sakana Fugu-Ultra |
|---|---|---|---|
| Agentic | MAI-Thinking-146.0 | Margin→ 36.1 | Sakana Fugu-Ultra82.1 |
| Knowledge | MAI-Thinking-172.5 | Margin→ 23.0 | Sakana Fugu-Ultra95.5 |
| Coding | MAI-Thinking-165.5 | Margin← 1.0 | Sakana Fugu-Ultra64.5 |
| Reasoning | MAI-Thinking-1Not measured | MarginNo overlap | Sakana Fugu-Ultra93.6 |
| Math | MAI-Thinking-189.7 | MarginNo overlap | Sakana Fugu-UltraNot measured |
| Multimodal | MAI-Thinking-1Not measured | MarginNo overlap | Sakana Fugu-Ultra86.6 |
| Inst. Following | MAI-Thinking-185.0 | 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 46%B 82.1%Winner: Sakana Fugu-UltraΔ 36.1Terminal-Bench 2.0: MAI-Thinking-1 scored 46%; Sakana Fugu-Ultra scored 82.1%. Sakana Fugu-Ultra wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 52.8%B 73.7%Winner: Sakana Fugu-UltraΔ 20.9SWE-bench Pro: MAI-Thinking-1 scored 52.8%; Sakana Fugu-Ultra scored 73.7%. Sakana Fugu-Ultra wins this benchmark. - Source ↗
GPQA
KnowledgeA 84.2%B 95.5%Winner: Sakana Fugu-UltraΔ 11.3GPQA: MAI-Thinking-1 scored 84.2%; 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 | MAI-Thinking-1 | Sakana Fugu-Ultra | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MAI-Thinking-1Not available | Sakana Fugu-UltraNot available | A complete price comparison is not available. |
| Generation speedtokens per second | MAI-Thinking-1Not available | Sakana Fugu-UltraNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | MAI-Thinking-1Not available | Sakana Fugu-UltraNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | MAI-Thinking-1256K | Sakana Fugu-Ultra1M | Sakana Fugu-Ultra lists the larger context window. |
Benchmark Deep Dive
AgenticSakana Fugu-Ultra wins1 benchmarks
| Benchmark | MAI-Thinking-1 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 46% | 82.1% | Sakana Fugu-Ultra leads |
CodingMAI-Thinking-1 wins6 benchmarks
| Benchmark | MAI-Thinking-1 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.5% | — | Not comparable |
| SWE-bench ProSource | 52.8% | 73.7% | Sakana Fugu-Ultra leads |
| Terminal-Bench 2.0Source | 46.0% | 82.1% | Sakana Fugu-Ultra leads |
| LiveCodeBench v6Source | — | 93.2% | Not comparable |
| LiveCodeBench ProSource | — | 90.8% | Not comparable |
| SciCodeSource | — | 58.7% | Not comparable |
Reasoning2 benchmarks
KnowledgeSakana Fugu-Ultra wins5 benchmarks
Math3 benchmarks
Multimodal1 benchmarks
| Benchmark | MAI-Thinking-1 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| CharXivSource | — | 86.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | MAI-Thinking-1 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| IFBenchSource | 85% | — | Not comparable |
Frequently Asked Questions (4)
Which is better, MAI-Thinking-1 or Sakana Fugu-Ultra?
MAI-Thinking-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, MAI-Thinking-1 or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for knowledge tasks in this comparison, averaging 95.5 versus 72.5. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, MAI-Thinking-1 or Sakana Fugu-Ultra?
MAI-Thinking-1 has the edge for coding in this comparison, averaging 65.5 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, MAI-Thinking-1 or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for agentic tasks in this comparison, averaging 82.1 versus 46. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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