Model comparison
o3-mini vs Sakana Fugu-Ultra
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: o3-mini #136 (Supported); Sakana Fugu-Ultra unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. o3-mini and Sakana Fugu-Ultra share 1 comparable benchmark result. 2 of 8 categories are comparable. 9 results are unique to o3-mini; 10 to Sakana Fugu-Ultra.
Updated July 23, 2026- Shared results
- 1
- o3-mini only
- 9
- Sakana Fugu-Ultra only
- 10
- Comparable categories
- 2 / 8
Treat this as a split decision. o3-mini makes more sense if its workflow fits your team better; Sakana Fugu-Ultra is the better fit if knowledge is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
o3-mini 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 200K for o3-mini.
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 | o3-mini | Δ | Sakana Fugu-Ultra |
|---|---|---|---|
| Knowledge | o3-mini77.2 | Margin→ 18.3 | Sakana Fugu-Ultra95.5 |
| Coding | o3-mini49.3 | Margin→ 15.2 | Sakana Fugu-Ultra64.5 |
| Agentic | o3-miniNot measured | MarginNo overlap | Sakana Fugu-Ultra82.1 |
| Reasoning | o3-miniNot measured | MarginNo overlap | Sakana Fugu-Ultra93.6 |
| Multimodal | o3-miniNot measured | MarginNo overlap | Sakana Fugu-Ultra86.6 |
| Inst. Following | o3-mini93.9 | MarginNo overlap | Sakana Fugu-UltraNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 77.2%B 95.5%Winner: Sakana Fugu-UltraΔ 18.3GPQA: o3-mini scored 77.2%; 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 | o3-mini | Sakana Fugu-Ultra | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | o3-mini$1.1 input / $4.4 output | Sakana Fugu-UltraNot available | A complete price comparison is not available. |
| Generation speedtokens per second | o3-mini160 tok/s | Sakana Fugu-UltraNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | o3-mini7.12 s | Sakana Fugu-UltraNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | o3-mini200K | Sakana Fugu-Ultra1M | Sakana Fugu-Ultra lists the larger context window. |
Benchmark Deep Dive
Agentic2 benchmarks
CodingSakana Fugu-Ultra wins7 benchmarks
| Benchmark | o3-mini | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 49.3% | — | Not comparable |
| AA-SciCodeSource | 39.9% | — | 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 |
Reasoning1 benchmarks
| Benchmark | o3-mini | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| MRCRv2Source | — | 93.6% | Not comparable |
KnowledgeSakana Fugu-Ultra wins7 benchmarks
| Benchmark | o3-mini | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| MMLUSource | 86.9% | — | Not comparable |
| GPQASource | 77.2% | 95.5% | Sakana Fugu-Ultra leads |
| Artificial Analysis Intelligence IndexSource | 19.0% | — | Not comparable |
| AA-GPQA DiamondSource | 74.8% | — | Not comparable |
| AA-HLESource | 8.7% | — | Not comparable |
| GPQA-DSource | — | 95.5% | Not comparable |
| HLE w/o toolsSource | — | 50% | Not comparable |
Math1 benchmarks
| Benchmark | o3-mini | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| AIME 2024Source | 87.3% | — | Not comparable |
Multimodal1 benchmarks
| Benchmark | o3-mini | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| CharXivSource | — | 86.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | o3-mini | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| IFEvalSource | 93.9% | — | Not comparable |
Frequently Asked Questions (3)
Which is better, o3-mini or Sakana Fugu-Ultra?
o3-mini 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, o3-mini or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for knowledge tasks in this comparison, averaging 95.5 versus 77.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, o3-mini or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for coding in this comparison, averaging 64.5 versus 49.3. o3-mini stays close enough that the answer can still flip depending on your workload.
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