UnifyBench

RankingEffort benchmarks

o3-pro effort benchmarks

Compare measured Low, Medium, High and other settings. Every number keeps its source.

o3-pro

4 measured results · 4 reported effort labels · 2 benchmark/harness combinations. Model evidence and sources →

Capability score evidence

o3-pro · Reasoning: 19.6 overall comparison score. Needs 3 benchmark families, 2 independently measured families

Which sources carry the weight?
  • Artificial Analysis · 100.0% direct comparison weight · independent

These shares describe the comparisons entering the fit, not fractions of the final score.

This configuration did not qualify for the dated stability audit.

What evidence is missing from the fit?

Across all collected settings for this model: 5 observations, 4 contributing, 0 matched without graph weight and 1 excluded. Counts do not establish rank eligibility.

  • 1 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately
Inspect every observation and exclusion →

Capability profile

One configuration, seven capabilities

Comparison score · 0–100
o3-pro · Reasoning 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 context50100o3-pro · Reasoning · Hard reasoning: 20.8 · Preliminary

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

  • Agentic

    Unknown

  • Hard reasoning

    A20.8Preliminary

  • 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.

Compare this configuration →Explore the model evidence profile →

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 / sourceLowMediumHighReasoning
GPQA DiamondArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

Unit: percent. Source collected 2026-09-12.

Not reportedNot reportedNot reported
84.55%
Reported settings

o3-pro; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/o3-pro; Mode from evaluator isReasoning metadata; effort budget not specified

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

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

Unit: percent. Source collected 2026-09-12.

2.05%
Reported settings

o3-Pro (Low); Source model ID: o3-pro-2025-06-10-low; 120 tasks

1.94%
Reported settings

o3-Pro (Medium); Source model ID: o3-pro-2025-06-10-medium; 120 tasks

4.86%
Reported settings

o3-Pro (High); Source model ID: o3-pro-2025-06-10-high; 120 tasks

Not reported
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 · 7,424 results across 240 models · Collected 2026-09-12