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Model comparison

GLM-5.2 vs Sakana Fugu-Ultra

Data verified

Head-to-head evidence from 6 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

63.96/100
No comparison
N/A
0 category wins3 category wins

Public leaderboard positions: GLM-5.2 #37 (Estimated); Sakana Fugu-Ultra unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-5.2 and Sakana Fugu-Ultra share 6 comparable benchmark results. 3 of 8 categories are comparable. 37 results are unique to GLM-5.2; 5 to Sakana Fugu-Ultra.

Updated July 23, 2026
Shared results
6
GLM-5.2 only
37
Sakana Fugu-Ultra only
5
Comparable categories
3 / 8

Treat this as a split decision. GLM-5.2 makes more sense if its workflow fits your team better; Sakana Fugu-Ultra is the better fit if knowledge is the priority.

Confidence note. This is a partial-evidence comparison with 6 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

GLM-5.2 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.

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 GLM-5.2 and Sakana Fugu-Ultra
CategoryGLM-5.2ΔSakana Fugu-Ultra
KnowledgeGLM-5.259.6Margin→ 35.9Sakana Fugu-Ultra95.5
CodingGLM-5.262.1Margin→ 2.4Sakana Fugu-Ultra64.5
AgenticGLM-5.281.0Margin→ 1.1Sakana Fugu-Ultra82.1
ReasoningGLM-5.2Not measuredMarginNo overlapSakana Fugu-Ultra93.6
MathGLM-5.295.9MarginNo overlapSakana Fugu-UltraNot measured
MultimodalGLM-5.2Not measuredMarginNo overlapSakana Fugu-Ultra86.6

Decisive benchmark drivers

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

More
A · GLM-5.2B · Sakana Fugu-Ultra

  1. SWE-bench Pro

    Coding
    Source ↗
    A 62.1%B 73.7%
    Winner: Sakana Fugu-UltraΔ 11.6
    SWE-bench Pro: GLM-5.2 scored 62.1%; Sakana Fugu-Ultra scored 73.7%. Sakana Fugu-Ultra wins this benchmark.

  2. GPQA

    Knowledge
    Source ↗
    A 91.2%B 95.5%
    Winner: Sakana Fugu-UltraΔ 4.3
    GPQA: GLM-5.2 scored 91.2%; Sakana Fugu-Ultra scored 95.5%. Sakana Fugu-Ultra wins this benchmark.

  3. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 81%B 82.1%
    Winner: Sakana Fugu-UltraΔ 1.1
    Terminal-Bench 2.0: GLM-5.2 scored 81%; Sakana Fugu-Ultra scored 82.1%. Sakana Fugu-Ultra wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGLM-5.2Sakana Fugu-UltraComparison
Input / output priceUSD per 1M tokensGLM-5.2$1.4 input / $4.4 outputSakana Fugu-UltraNot availableA complete price comparison is not available.
Generation speedtokens per secondGLM-5.2Not availableSakana Fugu-UltraNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGLM-5.2Not availableSakana Fugu-UltraNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGLM-5.21MSakana Fugu-Ultra1MListed context windows are equal.

Benchmark Deep Dive

AgenticSakana Fugu-Ultra wins
BenchmarkGLM-5.2Sakana Fugu-UltraResult
Terminal-Bench 2.0Source 81%82.1%Sakana Fugu-Ultra leads
MCP AtlasSource 76.8%—Not comparable
ToolathlonSource 48.2%—Not comparable
AA Agentic IndexSource 43.1%—Not comparable
τ²-bench resultsSource 99.1%—Not comparable
GDPval-AASource 50.7%—Not comparable
GDPval-AASource 1514—Not comparable
APEX-Agents-AASource 33.7%—Not comparable
ResearchClawBenchSource 20.7%—Not comparable
AA BriefcaseSource 1260—Not comparable
AA AutomationBenchSource 27.8%—Not comparable
AA EnterpriseOps-GymSource 42.7%—Not comparable
AA Harvey LABSource 91.0%—Not comparable
AA ITBenchSource 42.7%—Not comparable
AA Tau3 BankingSource 26.8%—Not comparable
terminalBenchHardSource 50.8%—Not comparable
aaTerminalBench21Source 77.9%—Not comparable
CodingSakana Fugu-Ultra wins
BenchmarkGLM-5.2Sakana Fugu-UltraResult
SWE-bench ProSource 62.1%73.7%Sakana Fugu-Ultra leads
NL2RepoSource 48.9%—Not comparable
Terminal-Bench 2.0Source 81.0%82.1%Sakana Fugu-Ultra leads
ProgramBenchSource 63.7%—Not comparable
cursorBench32Source 55.0%—Not comparable
AA Coding IndexSource 68.8%—Not comparable
AA-SciCodeSource 50.5%—Not comparable
LiveCodeBench v6Source —93.2%Not comparable
LiveCodeBench ProSource —90.8%Not comparable
SciCodeSource —58.7%Not comparable
Reasoning
BenchmarkGLM-5.2Sakana Fugu-UltraResult
CritPtSource 20.9%—Not comparable
AA-LCRSource 71.3%—Not comparable
MRCRv2Source —93.6%Not comparable
KnowledgeSakana Fugu-Ultra wins
BenchmarkGLM-5.2Sakana Fugu-UltraResult
GPQASource 91.2%95.5%Sakana Fugu-Ultra leads
GPQA-DSource 91.2%95.5%Sakana Fugu-Ultra leads
HLESource 54.7%—Not comparable
HLE w/o toolsSource 40.5%50%Sakana Fugu-Ultra leads
Artificial Analysis Intelligence IndexSource 51.1%—Not comparable
AA-GPQA DiamondSource 89.5%—Not comparable
AA-HLESource 40.1%—Not comparable
AA-Omniscience IndexSource 4.0%—Not comparable
AA-Omniscience AccuracySource 25.1%—Not comparable
AA-Omniscience Hallucination RateSource 28.1%—Not comparable
AA Openness IndexSource 44.4%—Not comparable
Math
BenchmarkGLM-5.2Sakana Fugu-UltraResult
AIME26Source 99.2%—Not comparable
HMMT Nov 2025Source 94.4%—Not comparable
HMMT Feb 2026Source 92.5%—Not comparable
MMAnswerBenchSource 91.0%—Not comparable
Multimodal
BenchmarkGLM-5.2Sakana Fugu-UltraResult
Design Arena WebsiteSource 1340—Not comparable
CharXivSource —86.6%Not comparable
Inst. Following
BenchmarkGLM-5.2Sakana Fugu-UltraResult
AA-IFBenchSource 73.3%—Not comparable
Frequently Asked Questions (4)

Which is better, GLM-5.2 or Sakana Fugu-Ultra?

GLM-5.2 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, GLM-5.2 or Sakana Fugu-Ultra?

Sakana Fugu-Ultra has the edge for knowledge tasks in this comparison, averaging 95.5 versus 59.6. Inside this category, HLE w/o tools is the benchmark that creates the most daylight between them.

Which is better for coding, GLM-5.2 or Sakana Fugu-Ultra?

Sakana Fugu-Ultra has the edge for coding in this comparison, averaging 64.5 versus 62.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, GLM-5.2 or Sakana Fugu-Ultra?

Sakana Fugu-Ultra has the edge for agentic tasks in this comparison, averaging 82.1 versus 81. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

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Last updated: July 23, 2026

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