Model comparison
MiniMax M3 vs Sakana Fugu-Ultra
Head-to-head evidence from 3 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: MiniMax M3 #15 (Supported); Sakana Fugu-Ultra unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. MiniMax M3 and Sakana Fugu-Ultra share 3 comparable benchmark results. 3 of 8 categories are comparable. 42 results are unique to MiniMax M3; 8 to Sakana Fugu-Ultra.
Updated July 23, 2026- Shared results
- 3
- MiniMax M3 only
- 42
- Sakana Fugu-Ultra only
- 8
- Comparable categories
- 3 / 8
Treat this as a split decision. MiniMax M3 makes more sense if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model; Sakana Fugu-Ultra is the better fit if multimodal & grounded is the priority or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 2 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
MiniMax M3 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 is the reasoning model in the pair, while MiniMax M3 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use.
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 | MiniMax M3 | Δ | Sakana Fugu-Ultra |
|---|---|---|---|
| Multimodal | MiniMax M364.9 | Margin→ 21.7 | Sakana Fugu-Ultra86.6 |
| Agentic | MiniMax M372.3 | Margin→ 9.8 | Sakana Fugu-Ultra82.1 |
| Coding | MiniMax M372.2 | Margin← 7.7 | Sakana Fugu-Ultra64.5 |
| Reasoning | MiniMax M3Not measured | MarginNo overlap | Sakana Fugu-Ultra93.6 |
| Knowledge | MiniMax M3Not measured | MarginNo overlap | Sakana Fugu-Ultra95.5 |
| Math | MiniMax M385.7 | 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 66%B 82.1%Winner: Sakana Fugu-UltraΔ 16.1Terminal-Bench 2.0: MiniMax M3 scored 66%; Sakana Fugu-Ultra scored 82.1%. Sakana Fugu-Ultra wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 59%B 73.7%Winner: Sakana Fugu-UltraΔ 14.7SWE-bench Pro: MiniMax M3 scored 59%; Sakana Fugu-Ultra scored 73.7%. Sakana Fugu-Ultra wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | MiniMax M3 | Sakana Fugu-Ultra | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MiniMax M3$0.3 input / $1.2 output | Sakana Fugu-UltraNot available | A complete price comparison is not available. |
| Generation speedtokens per second | MiniMax M3Not available | Sakana Fugu-UltraNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | MiniMax M3Not available | Sakana Fugu-UltraNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | MiniMax M31M | Sakana Fugu-Ultra1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticSakana Fugu-Ultra wins18 benchmarks
| Benchmark | MiniMax M3 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 66% | 82.1% | Sakana Fugu-Ultra leads |
| BrowseCompSource | 83.5% | — | Not comparable |
| OSWorld-VerifiedSource | 70.1% | — | Not comparable |
| MCP AtlasSource | 74.2% | — | Not comparable |
| Claw-EvalSource | 74.5% | — | Not comparable |
| AA Agentic IndexSource | 35.4% | — | Not comparable |
| τ²-bench resultsSource | 88.9% | — | Not comparable |
| GDPval-AASource | 44.7% | — | Not comparable |
| GDPval-AASource | 1395 | — | Not comparable |
| GDPval rubricsSource | 74.7% | — | Not comparable |
| BankerToolBenchSource | 76.1% | — | Not comparable |
| ResearchClawBenchSource | 19.8% | — | Not comparable |
| OSWorld 2.0Source | 4.6% | — | Not comparable |
| AA BriefcaseSource | 1110 | — | Not comparable |
| AA EnterpriseOps-GymSource | 32.1% | — | Not comparable |
| AA Harvey LABSource | 88.4% | — | Not comparable |
| terminalBenchHardSource | 42.4% | — | Not comparable |
| aaTerminalBench21Source | 65.2% | — | Not comparable |
CodingMiniMax M3 wins12 benchmarks
| Benchmark | MiniMax M3 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.5% | — | Not comparable |
| SWE-bench ProSource | 59% | 73.7% | Sakana Fugu-Ultra leads |
| Terminal-Bench 2.0Source | 66.0% | 82.1% | Sakana Fugu-Ultra leads |
| NL2RepoSource | 42.1% | — | Not comparable |
| AA Coding IndexSource | 58.6% | — | Not comparable |
| AA-SciCodeSource | 45.4% | — | Not comparable |
| VIBE V2Source | 50.1% | — | Not comparable |
| SVG-BenchSource | 63.7% | — | Not comparable |
| KernelBench HardSource | 28.8% | — | Not comparable |
| LiveCodeBench v6Source | — | 93.2% | Not comparable |
| LiveCodeBench ProSource | — | 90.8% | Not comparable |
| SciCodeSource | — | 58.7% | Not comparable |
Reasoning3 benchmarks
Knowledge10 benchmarks
| Benchmark | MiniMax M3 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 44.4% | — | Not comparable |
| AA-GPQA DiamondSource | 92.9% | — | Not comparable |
| AA-HLESource | 37.1% | — | Not comparable |
| AA-Omniscience IndexSource | 1.4% | — | Not comparable |
| AA-Omniscience AccuracySource | 15.0% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 16.1% | — | Not comparable |
| AA Openness IndexSource | 33.3% | — | Not comparable |
| GPQASource | — | 95.5% | Not comparable |
| GPQA-DSource | — | 95.5% | Not comparable |
| HLE w/o toolsSource | — | 50% | Not comparable |
Math1 benchmarks
| Benchmark | MiniMax M3 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| USAMO 2026Source | 85.7% | — | Not comparable |
MultimodalSakana Fugu-Ultra wins8 benchmarks
| Benchmark | MiniMax M3 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| OfficeQA ProSource | 45.1% | — | Not comparable |
| OmniDocBench 1.5Source | 91.6% | — | Not comparable |
| MMMU-ProSource | 78.1% | — | Not comparable |
| VideoMMMUSource | 84.6% | — | Not comparable |
| Video-MME (with subtitle)Source | 85.4% | — | Not comparable |
| Design Arena WebsiteSource | 1289 | — | Not comparable |
| AA-MMMU-ProSource | 78.6% | — | Not comparable |
| CharXivSource | — | 86.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | MiniMax M3 | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| AA-IFBenchSource | 82.9% | — | Not comparable |
Frequently Asked Questions (4)
Which is better, MiniMax M3 or Sakana Fugu-Ultra?
MiniMax M3 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 coding, MiniMax M3 or Sakana Fugu-Ultra?
MiniMax M3 has the edge for coding in this comparison, averaging 72.2 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, MiniMax M3 or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for agentic tasks in this comparison, averaging 82.1 versus 72.3. 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, MiniMax M3 or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for multimodal and grounded tasks in this comparison, averaging 86.6 versus 64.9. MiniMax M3 stays close enough that the answer can still flip depending on your workload.
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