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Model comparison

DeepSeek V3 vs Sakana Fugu-Ultra

Data verified

Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

DeepSeek
44.97/100
No comparison
N/A
0 category wins2 category wins

Public leaderboard positions: DeepSeek V3 #147 (Supported); Sakana Fugu-Ultra unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V3 and Sakana Fugu-Ultra share 1 comparable benchmark result. 2 of 8 categories are comparable. 21 results are unique to DeepSeek V3; 10 to Sakana Fugu-Ultra.

Updated July 23, 2026
Shared results
1
DeepSeek V3 only
21
Sakana Fugu-Ultra only
10
Comparable categories
2 / 8

Treat this as a split decision. DeepSeek V3 makes more sense if you would rather avoid the extra latency and token burn of a reasoning model; Sakana Fugu-Ultra is the better fit if coding 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

DeepSeek V3 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 DeepSeek V3 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. Sakana Fugu-Ultra gives you the larger context window at 1M, compared with 128K for DeepSeek V3.

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 scores and score margins for DeepSeek V3 and Sakana Fugu-Ultra
CategoryDeepSeek V3ΔSakana Fugu-Ultra
CodingDeepSeek V338.9Margin 25.6Sakana Fugu-Ultra64.5
KnowledgeDeepSeek V372.7Margin 22.8Sakana Fugu-Ultra95.5
AgenticDeepSeek V3Not measuredMarginNo overlapSakana Fugu-Ultra82.1
ReasoningDeepSeek V3Not measuredMarginNo overlapSakana Fugu-Ultra93.6
MathDeepSeek V31.7MarginNo overlapSakana Fugu-UltraNot measured
MultimodalDeepSeek V3Not measuredMarginNo overlapSakana Fugu-Ultra86.6
Inst. FollowingDeepSeek V386.1MarginNo overlapSakana Fugu-UltraNot measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · DeepSeek V3B · Sakana Fugu-Ultra
  1. GPQA

    Knowledge
    Source ↗
    A 59.1%B 95.5%
    Winner: Sakana Fugu-UltraΔ 36.4
    GPQA: DeepSeek V3 scored 59.1%; 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.

MetricDeepSeek V3Sakana Fugu-UltraComparison
Input / output priceUSD per 1M tokensDeepSeek V3$0.27 input / $1.1 outputSakana Fugu-UltraNot availableA complete price comparison is not available.
Generation speedtokens per secondDeepSeek V3Not availableSakana Fugu-UltraNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenDeepSeek V3Not availableSakana Fugu-UltraNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensDeepSeek V3128KSakana Fugu-Ultra1MSakana Fugu-Ultra lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkDeepSeek V3Sakana Fugu-UltraResult
AA Agentic IndexSource 1.6%Not comparable
τ²-bench resultsSource 22.8%Not comparable
GDPval-AASource 0.0%Not comparable
GDPval-AASource 217Not comparable
Terminal-Bench 2.0Source 82.1%Not comparable
CodingSakana Fugu-Ultra wins
BenchmarkDeepSeek V3Sakana Fugu-UltraResult
LiveCodeBenchSource 37.6%Not comparable
SWE-bench VerifiedSource 42%Not comparable
AA Coding IndexSource 23.0%Not comparable
AA-SciCodeSource 35.4%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
Reasoning
BenchmarkDeepSeek V3Sakana Fugu-UltraResult
AA-LCRSource 29.0%Not comparable
CritPtSource 0.0%Not comparable
MRCRv2Source 93.6%Not comparable
KnowledgeSakana Fugu-Ultra wins
BenchmarkDeepSeek V3Sakana Fugu-UltraResult
GPQASource 59.1%95.5%Sakana Fugu-Ultra leads
MMLU-ProSource 75.9%Not comparable
Artificial Analysis Intelligence IndexSource 14.2%Not comparable
AA-GPQA DiamondSource 55.7%Not comparable
AA-HLESource 3.6%Not comparable
AA-Omniscience IndexSource -41.3%Not comparable
AA-Omniscience AccuracySource 25.4%Not comparable
AA-Omniscience Hallucination RateSource 89.4%Not comparable
GPQA-DSource 95.5%Not comparable
HLE w/o toolsSource 50%Not comparable
Math
BenchmarkDeepSeek V3Sakana Fugu-UltraResult
FrontierMath v2 (Tiers 1-3)Source 1.724%Not comparable
Multimodal
BenchmarkDeepSeek V3Sakana Fugu-UltraResult
Design Arena WebsiteSource 1150Not comparable
CharXivSource 86.6%Not comparable
Inst. Following
BenchmarkDeepSeek V3Sakana Fugu-UltraResult
IFEvalSource 86.1%Not comparable
AA-IFBenchSource 34.8%Not comparable
Frequently Asked Questions (3)

Which is better, DeepSeek V3 or Sakana Fugu-Ultra?

DeepSeek V3 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, DeepSeek V3 or Sakana Fugu-Ultra?

Sakana Fugu-Ultra has the edge for knowledge tasks in this comparison, averaging 95.5 versus 72.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.

Which is better for coding, DeepSeek V3 or Sakana Fugu-Ultra?

Sakana Fugu-Ultra has the edge for coding in this comparison, averaging 64.5 versus 38.9. DeepSeek V3 stays close enough that the answer can still flip depending on your workload.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

DeepSeek V3
API / mo$1,028
Self-host / mo$18,221
Break-even1.2B/day
Sakana Fugu-Ultra
API / mo$0
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Model the full break-even

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Last updated: July 23, 2026

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