UnifyBench

RankingEffort benchmarks

GPT-5.5 Pro · XHigh

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6 measured results · 2 effort settings · 5 benchmark/harness combinations

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Choose a second model and its effort to see both profiles and benchmark differences below.

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Capability profile

One configuration, seven capabilities

Comparison score · 0–100
GPT-5.5 Pro · XHigh capability radarComparison scores from 0 to 100. Unknown capabilities have no point; lines stop at gaps. Hollow points are preliminary. Exact values and support labels follow the chart.AgenticHard reasoningCodingHuman prefKnowledgeMultimodalLong context50100GPT-5.5 Pro · XHigh · Hard reasoning: 70.9 · Supported

Gaps are unknown, not zero. Hollow points are preliminary.

  • Agentic

    Unknown

  • Hard reasoning

    A70.9Supported

  • Coding

    Unknown

  • Human pref

    Unknown

  • Knowledge

    Unknown

  • Multimodal

    Unknown

  • Long context

    Unknown

Each profile belongs to the named configuration. Capability scores use a shared panel for all axes, distinct from the overall ranking panel; they are not accuracy percentages or direct head-to-head wins.

Capability score evidence

GPT-5.5 Pro · XHigh: 76.5 overall comparison score. Meets the overall evidence requirements.

Hard reasoning only. The available task mix affects this estimate; missing areas remain unknown.

Shared-result disagreement. This aggregate order conflicts with matched benchmark results against 1 other configurations. Different test coverage and opponents affect the fit. Inspect published results before treating the rank as conclusive.

Which sources carry the weight?
  • ARC Prize · 59.1% direct comparison weight · independent of the model provider
  • Artificial Analysis · 21.0% direct comparison weight · independent of the model provider
  • Epoch AI · 19.9% direct comparison weight · independent of the model provider
Which benchmark families carry the weight?
  • ARC-AGI · 59.1% direct comparison weight
  • Critpt · 21.0% direct comparison weight
  • FrontierMath · 19.9% direct comparison weight

These shares describe direct comparison weight, not fractions of the final score or confidence. Source balancing does not give every family equal weight or remove correlations between overlapping sources.

How sensitive is this score?

The audit removes one source at a time and refits against the same overall reference panel. These published results use the matching dataset audited 2026-10-20.

Both ranks use the same surviving configurations for each removal. The cohort starts with 444 configurations supported in the original audit, including separate effort settings. These are diagnostic positions, not the default leaderboard ranks. Eligibility is not rechecked after removal.

What changes when a source is removed?
Removed sourceRank before → afterRank movementCohort remaining / lost supportScore after (change)
Artificial Analysis27 → 27No movement203 remaining / 241 lost77.0 (+0.5 points)
ARC Prize27 → 27No movement444 remaining / 0 lost79.1 (+2.7 points)
Datacurve27 → 28Down 1444 remaining / 0 lost74.1 (-2.3 points)
LiveCodeBench27 → 27No movement444 remaining / 0 lost76.5 (+0.0 points)
Scale27 → 27No movement444 remaining / 0 lost77.2 (+0.8 points)
Terminal-Bench27 → 26Up 1444 remaining / 0 lost76.4 (-0.1 points)
Cognition27 → 25Up 2444 remaining / 0 lost74.8 (-1.7 points)
LiveBench27 → 29Down 2443 remaining / 1 lost76.9 (+0.4 points)
SWE-rebench27 → 26Up 1444 remaining / 0 lost76.2 (-0.3 points)
Epoch AI27 → 29Down 2431 remaining / 13 lost76.0 (-0.4 points)
Vals AI27 → 26Up 1443 remaining / 1 lost75.9 (-0.6 points)
Provider reports · Anthropic27 → 28Down 1444 remaining / 0 lost76.4 (-0.0 points)
Provider reports · Moonshot AI27 → 27No movement444 remaining / 0 lost76.1 (-0.3 points)
Provider reports · Meta27 → 27No movement444 remaining / 0 lost76.4 (-0.0 points)
Provider reports · Mistral27 → 27No movement444 remaining / 0 lost76.5 (+0.0 points)
Provider reports · OpenAI27 → 26Up 1444 remaining / 0 lost76.3 (-0.1 points)
All provider reports27 → 27No movement444 remaining / 0 lost76.0 (-0.5 points)

Lost support means a configuration no longer has a comparison path to the complete reference panel. Its rank is unavailable. A surviving path alone does not establish leaderboard eligibility.

Overlapping sources may remain correlated even with source balancing. Leave-one-source-out movement is a sensitivity diagnostic, not a spread of source-specific ranks or a confidence measure. Scoring methodology · Dated configuration audit

Every benchmark family
Removed evidenceRecomputed scoreChange
deepswe74.2-2.3
arc-agi78.2+1.8
frontiercode74.8-1.7
arc-agi-375.0-1.4
simpleqa77.6+1.1
critpt77.3+0.9
frontiermath75.9-0.5
mmmu-pro77.0+0.5
hle76.8+0.3
ifbench76.1-0.3
swe-rebench76.2-0.3
tau-bench76.2-0.3
epoch-game-puzzles76.2-0.2
gdp-pdf76.7+0.2
livebench-instructions76.7+0.2
swe-atlas-test-writing76.3-0.2
mmlu-pro76.6+0.2
multi-swe-bench76.3-0.2
swe-atlas-qna76.3-0.2
livebench-coding76.3-0.1
livebench-language76.6+0.1
terminal-bench76.4-0.1
vibe-code76.4-0.1
gpqa76.5+0.1
harvey76.4-0.1
livecodebench76.4-0.1
livebench-reasoning76.4-0.1
apex-agents76.5+0.1
livebench-data76.5+0.1
vals-legal-research76.4-0.1
enigma-eval76.4-0.1
aa-lcr76.4-0.1
swe-atlas-refactoring76.4-0.1
aime76.5+0.0
automationbench76.4-0.0
analyst-agent76.5+0.0
vals-excel-modeling76.4-0.0
vals-tax-agent76.4-0.0
gmmlu76.4-0.0
terminal-bench-science76.5+0.0
math50076.4-0.0
omniscience76.5+0.0
briefcase76.4-0.0
vals-code-migration76.4-0.0
gdpval76.5+0.0
livebench-math76.4-0.0
enterprise-ops76.5+0.0
vals-finance-agent76.5+0.0
itbench76.5+0.0
swe-bench-pro76.5-0.0
What evidence is missing from the fit?

Across all collected settings for this model: 7 observations, 5 contributing, 0 matched without graph weight and 2 excluded. Counts do not establish rank eligibility.

  • 1 · Benchmark family or source protocol has not been reviewed
  • 1 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately
Inspect every observation and exclusion →

Benchmark results

These are published benchmark scores. Supported effort estimates also appear on the Capability leaderboard. Results from different harnesses occupy different rows. Missing cells stay unknown; no scores are copied between effort levels.

Benchmark / sourceHighXHigh
CritPtArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Benchmark developed by Argonne and UIUC, with contributions from 60+ researchers globally. CritPt is under review by its authors following external feedback · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

Unit: percent. Source collected 2026-10-18.

Not reported
30.57%
Reported settings

GPT-5.5 Pro (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-5-pro

ARC-AGI-2ARC Prize · v2 Semi-Private
Benchmark details

Original public board. Configuration and task coverage may differ; inspect source.

Unit: percent. Source collected 2026-10-18.

84.58%
Reported settings

GPT-5.5 Pro (High); Source model ID: gpt-5-5-pro-2026-04-23-high; 120 tasks

84.16%
Reported settings

GPT-5.5 Pro (XHigh); Source model ID: gpt-5-5-pro-2026-04-23-xhigh; 120 tasks

Epoch · Chess Puzzles · v2.0.0Epoch AI · Epoch AI Inspect; task 2.0.0; scorer exact
Benchmark details

Epoch AI internal evaluation. Mean accuracy under the published setting; exact task version and scorer stay separate. Related tasks share a family budget. Data by Epoch AI, CC BY.

Unit: percent. Source collected 2026-10-18.

Not reported
62%
Reported settings

Epoch AI Inspect; task 2.0.0; scorer exact; model=gpt-5.5-pro_xhigh; run=5u4XrDnQSRnuXSK6oXKAth; mean accuracy; https://epoch.ai/data/benchmarks.csv

Epoch · FrontierMath Tier 4 · v2.0.0Epoch AI · Epoch AI Inspect; task 2.0.0; scorer verification_code
Benchmark details

Epoch AI internal evaluation. Mean accuracy under the published setting; exact task version and scorer stay separate. Related tasks share a family budget. Data by Epoch AI, CC BY. FrontierMath was developed with OpenAI funding and unequal access to part of the question set; this result is from Epoch's evaluation.

Unit: percent. Source collected 2026-10-18.

Not reported
78.05%
Reported settings

Epoch AI Inspect; task 2.0.0; scorer verification_code; model=gpt-5.5-pro_xhigh; run=SFKXCPUu73mwxMoUotiZM2; mean accuracy; https://epoch.ai/data/benchmarks.csv

Epoch · FrontierMath Tiers 1–3 · v2.0.0Epoch AI · Epoch AI Inspect; task 2.0.0; scorer verification_code
Benchmark details

Epoch AI internal evaluation. Mean accuracy under the published setting; exact task version and scorer stay separate. Related tasks share a family budget. Data by Epoch AI, CC BY. FrontierMath was developed with OpenAI funding and unequal access to part of the question set; this result is from Epoch's evaluation.

Unit: percent. Source collected 2026-10-18.

Not reported
87.72%
Reported settings

Epoch AI Inspect; task 2.0.0; scorer verification_code; model=gpt-5.5-pro_xhigh; run=LSKDetgzyVojru45w7RJhf; mean accuracy; https://epoch.ai/data/benchmarks.csv

What these comparisons mean

Each source reports its own effort labels. Matching labels do not establish equal compute budgets or identical fallback behavior. Open Reported settings to inspect the exact model name, agent and task coverage. Multiple results at one level remain visible rather than selecting the best. Source-reported None or Non-reasoning labels are not treated as evidence that an API supports those settings.

These measurements use their own dated source collection. The leaderboard fits identified configurations jointly; it contains no pooled model ratings. Explicit thinking budgets are separate configurations. Read the methodology.

Download all effort benchmark results · 8,915 results across 259 models · Collected 2026-10-18