RankingEffort benchmarks

o3-mini effort benchmarks

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

Model

o3-mini

32 measured results · 4 reported effort labels · 22 benchmark/harness combinations. Model evidence and sources →

Capability score evidence

o3-mini · High: 5.8 overall comparison score. Meets the overall evidence requirements.

Which sources carry the weight?

Artificial Analysis · 42.2% direct comparison weight · independent
ARC Prize · 36.2% direct comparison weight · independent
Scale · 21.6% direct comparison weight · independent

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

How sensitive is this score?

Remove one evaluator or family and refit the graph against the same overall panel. Values use the matching dataset audited 2026-09-12. These are sensitivity checks, not confidence intervals; ranking eligibility may also change.

Removed evidence	Recomputed score	Change
Artificial Analysis	4.9	-0.9
ARC Prize	6.0	+0.2
Datacurve	4.9	-0.9
LiveCodeBench	5.8	-0.0
Scale	7.7	+1.9
Terminal-Bench	5.8	-0.0
Cognition	6.2	+0.4
LiveBench	5.9	+0.1
SWE-rebench	5.9	+0.1
Epoch AI	5.7	-0.1
Vals AI	5.6	-0.2
Provider reports · Anthropic	5.8	+0.0
Provider reports · Moonshot AI	5.8	-0.0
Provider reports · Meta	5.8	-0.0
Provider reports · Mistral	5.8	+0.0
All provider reports	5.8	-0.0

Every benchmark family

Removed evidence	Recomputed score	Change
hle	7.2	+1.4
deepswe	4.9	-0.9
mmmu-pro	6.2	+0.4
frontiercode	6.2	+0.4
epoch-game-puzzles	5.5	-0.3
omniscience	5.5	-0.3
ifbench	5.6	-0.2
mmlu-pro	6.0	+0.2
simpleqa	6.0	+0.2
arc-agi	6.0	+0.2
gdpval	5.9	+0.1
math500	5.7	-0.1
tau-bench	5.9	+0.1
automationbench	5.9	+0.1
terminal-bench	5.9	+0.1
enigma-eval	5.7	-0.1
gpqa	5.7	-0.1
multi-swe-bench	5.7	-0.1
livebench-instructions	5.9	+0.1
gdp-pdf	5.9	+0.1
swe-rebench	5.9	+0.1
livebench-language	5.9	+0.1
harvey	5.7	-0.1
critpt	5.7	-0.1
briefcase	5.9	+0.1
livecodebench	5.7	-0.1
frontiermath	5.9	+0.1
livebench-coding	5.8	-0.0
apex-agents	5.8	+0.0
swe-atlas-qna	5.8	-0.0
scicode	5.8	-0.0
aa-lcr	5.8	+0.0
vibe-code	5.8	-0.0
arc-agi-3	5.8	-0.0
livebench-reasoning	5.8	-0.0
vals-finance-agent	5.8	-0.0
vals-code-migration	5.8	-0.0
vals-legal-research	5.8	-0.0
swe-atlas-test-writing	5.8	-0.0
gmmlu	5.8	-0.0
analyst-agent	5.8	+0.0
aime	5.8	+0.0
vals-excel-modeling	5.8	-0.0
livebench-math	5.8	+0.0
livebench-data	5.8	+0.0
swe-atlas-refactoring	5.8	-0.0
itbench	5.8	-0.0
enterprise-ops	5.8	+0.0
swe-bench-pro	5.8	+0.0

What evidence is missing from the fit?

Across all collected settings for this model: 35 observations, 31 contributing, 0 matched without graph weight and 4 excluded. Counts do not establish rank eligibility.

1 · Benchmark family or source protocol has not been reviewed
3 · 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

Ao3-mini · High4 of 7 capabilities supported

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

Agentic
A4.5Supported
Hard reasoning
A8.6Supported
Coding
A7.0Supported
Human pref
Unknown
Knowledge
A12.4Supported
Multimodal
Unknown
Long context
A6.8Preliminary

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 / source	Low	Medium	High	Reasoning
AA-Briefcase EloArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details AA-Briefcase is an agentic knowledge work benchmark developed by Artificial Analysis. AA-Briefcase Elo is a combined metric that aggregates rubric pass rate, analytical quality Elo and presentation Elo · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-09-12.	Not reported	Not reported	161.06 Elo Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
AA-LCR v1.1Artificial 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 reported	Not reported	43% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
AutomationBench-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Share of task objectives completed with no guardrail violations · Higher is better · Benchmark developed by Zapier · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12.	Not reported	Not reported	0.53% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
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 · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12.	Not reported	Not reported	0.29% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
GDP.pdf: All-passArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Share of attempts where every atomic criterion passed · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12.	Not reported	Not reported	2% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
GDPval-AA v2 LeaderboardArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Elo rating for performance on real-world work tasks · Anchored to a human baseline of 1,000 · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-09-12.	Not reported	Not reported	420.79 Elo Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
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 reported	Not reported	77.27% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	74.85% Reported settings o3-mini; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/o3-mini; Mode from evaluator isReasoning metadata; effort budget not specified
Humanity's Last ExamArtificial 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 reported	Not reported	12.04% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	7.91% Reported settings o3-mini; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/o3-mini; Mode from evaluator isReasoning metadata; effort budget not specified
IFBenchArtificial 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 reported	Not reported	67.14% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
LiveCodeBenchArtificial 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 reported	Not reported	73.44% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	71.75% Reported settings o3-mini; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/o3-mini; Mode from evaluator isReasoning metadata; effort budget not specified
MATH-500Artificial 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 reported	Not reported	98.47% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	97.33% Reported settings o3-mini; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/o3-mini; Mode from evaluator isReasoning metadata; effort budget not specified
MMLU-ProArtificial 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 reported	Not reported	80.19% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	79.06% Reported settings o3-mini; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/o3-mini; Mode from evaluator isReasoning metadata; effort budget not specified
AA-Omniscience IndexArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct. · Evaluation results measured independently by Artificial Analysis Unit: index. Source collected 2026-09-12.	Not reported	Not reported	-42.57 Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
AA-Omniscience AccuracyArtificial Analysis · 6000 questions; 1 attempt; correct-answer share; GPT-5.6 Luna medium grader Benchmark details AA-Omniscience Accuracy (higher is better) measures the proportion of correctly answered questions out of all questions, regardless of whether the model chooses to answer · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12.	Not reported	Not reported	21.27% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
SciCodeArtificial 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 reported	Not reported	42.82% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
𝜏²-Bench TelecomArtificial 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 reported	Not reported	31.29% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	28.65% Reported settings o3-mini; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/o3-mini; Mode from evaluator isReasoning metadata; effort budget not specified
𝜏³-BankingArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Benchmark developed by Sierra Research · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12.	Not reported	Not reported	5.15% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
Terminal-Bench HardArtificial 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 reported	Not reported	6.06% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	6.82% Reported settings o3-mini; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/o3-mini; Mode from evaluator isReasoning metadata; effort budget not specified
Terminal-Bench v2.1Artificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Benchmark developed by the Laude Institute and open-source contributors · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12.	Not reported	Not reported	4.49% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
Terminal-Bench v4.0Artificial Analysis · mini-SWE-agent v2.4.6; 66 tasks; pass@1 averaged over 3 repeats; 500 steps; task timeout up to 8 hours Benchmark details Benchmark developed by the Laude Institute, Stanford, and open-source contributors · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12.	Not reported	Not reported	0% Reported settings o3-mini (high); Model source: https://artificialanalysis.ai/models/o3-mini-high	Not reported
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.	0% Reported settings o3-mini (Low); Source model ID: o3-mini-2025-01-31-low; 120 tasks	2.08% Reported settings o3-mini (Medium); Source model ID: o3-mini-2025-01-31-medium; 120 tasks	2.99% Reported settings o3-mini (High); Source model ID: o3-mini-2025-01-31-high; 120 tasks	Not reported
HLE · text only · Scale official evaluationScale · Scale official evaluation Benchmark details Scale text-only public HLE subset; shares the full HLE family budget; automatic answer judging. Unit: percent. Source collected 2026-09-12.	Not reported	10.31% Reported settings Scale text-only public HLE subset; shares the full HLE family budget; automatic answer judging.; published row 2025-04-10T19:29:02.000Z; reported margin ±1.28 percentage points; Potential contamination warning: This model was evaluated after the public release of HLE, allowing model builder access to the prompts and solutions.	13.37% Reported settings Scale text-only public HLE subset; shares the full HLE family budget; automatic answer judging.; published row 2025-04-10T19:29:02.000Z; reported margin ±1.44 percentage points; Potential contamination warning: This model was evaluated after the public release of HLE, allowing model builder access to the prompts and solutions.	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

o3-mini effort benchmarks

o3-mini

Capability score evidence

One configuration, seven capabilities

Agentic

Hard reasoning

Coding

Human pref

Knowledge

Multimodal

Long context