RankingEffort benchmarks

GPT-5 Mini · High

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60 measured results · 4 effort settings · 29 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

AGPT-5 Mini · High4 of 7 capabilities supported

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

Agentic
A15.6Supported
Hard reasoning
A11.9Supported
Coding
A13.0Supported
Human pref
Unknown
Knowledge
A19.9Supported
Multimodal
A12.7Preliminary
Long context
A27.8Preliminary

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.

Capability score evidence

GPT-5 Mini · High: 6.2 overall comparison score. Meets the overall evidence requirements.

6 areas measured. The available task mix affects this estimate; missing areas remain unknown.

Which sources carry the weight?

Artificial Analysis · 40.4% direct comparison weight · independent of the model provider
ARC Prize · 31.4% direct comparison weight · independent of the model provider
SWE-rebench · 28.2% direct comparison weight · independent of the model provider

Which benchmark families carry the weight?

ARC-AGI · 31.4% direct comparison weight
swe-rebench · 28.2% direct comparison weight
Aime · 2.4% direct comparison weight
MMLU-Pro · 2.4% direct comparison weight
LiveCodeBench · 2.4% direct comparison weight
Other families (14) · 33.0% 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 source	Rank before → after	Rank movement	Cohort remaining / lost support	Score after (change)
Artificial Analysis	162 → 170	Down 8	203 remaining / 241 lost	3.9 (-2.3 points)
ARC Prize	230 → 224	Up 6	444 remaining / 0 lost	8.2 (+2.0 points)
Datacurve	230 → 230	No movement	444 remaining / 0 lost	4.9 (-1.4 points)
LiveCodeBench	230 → 230	No movement	444 remaining / 0 lost	6.2 (-0.0 points)
Scale	230 → 230	No movement	444 remaining / 0 lost	7.2 (+1.0 points)
Terminal-Bench	230 → 230	No movement	444 remaining / 0 lost	6.1 (-0.1 points)
Cognition	230 → 232	Down 2	444 remaining / 0 lost	6.0 (-0.2 points)
LiveBench	229 → 229	No movement	443 remaining / 1 lost	6.3 (+0.1 points)
SWE-rebench	230 → 230	No movement	444 remaining / 0 lost	6.4 (+0.2 points)
Epoch AI	224 → 221	Up 3	431 remaining / 13 lost	6.6 (+0.4 points)
Vals AI	230 → 230	No movement	443 remaining / 1 lost	5.9 (-0.3 points)
Provider reports · Anthropic	230 → 230	No movement	444 remaining / 0 lost	6.2 (-0.0 points)
Provider reports · Moonshot AI	230 → 230	No movement	444 remaining / 0 lost	6.0 (-0.2 points)
Provider reports · Meta	230 → 230	No movement	444 remaining / 0 lost	6.2 (-0.0 points)
Provider reports · Mistral	230 → 230	No movement	444 remaining / 0 lost	6.2 (+0.0 points)
Provider reports · OpenAI	230 → 230	No movement	444 remaining / 0 lost	6.3 (+0.0 points)
All provider reports	230 → 230	No movement	444 remaining / 0 lost	6.1 (-0.1 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 evidence	Recomputed score	Change
arc-agi	7.9	+1.7
deepswe	4.9	-1.4
mmmu-pro	6.7	+0.5
hle	6.7	+0.5
critpt	6.6	+0.4
ifbench	5.9	-0.4
omniscience	5.9	-0.3
simpleqa	6.5	+0.3
arc-agi-3	6.0	-0.2
mmlu-pro	6.4	+0.2
frontiercode	6.0	-0.2
swe-rebench	6.4	+0.2
aa-lcr	6.1	-0.2
gpqa	6.1	-0.2
terminal-bench	6.4	+0.2
aime	6.1	-0.1
livebench-instructions	6.4	+0.1
multi-swe-bench	6.1	-0.1
briefcase	6.3	+0.1
livecodebench	6.1	-0.1
livebench-language	6.3	+0.1
apex-agents	6.3	+0.1
enigma-eval	6.1	-0.1
gmmlu	6.1	-0.1
harvey	6.1	-0.1
swe-atlas-qna	6.1	-0.1
livebench-coding	6.1	-0.1
terminal-bench-science	6.3	+0.1
epoch-game-puzzles	6.2	-0.1
livebench-reasoning	6.2	-0.0
vibe-code	6.2	-0.0
analyst-agent	6.3	+0.0
tau-bench	6.2	-0.0
swe-atlas-test-writing	6.2	-0.0
vals-code-migration	6.2	-0.0
vals-finance-agent	6.2	-0.0
vals-legal-research	6.2	-0.0
vals-tax-agent	6.2	-0.0
itbench	6.2	-0.0
gdpval	6.2	+0.0
math500	6.2	+0.0
enterprise-ops	6.2	+0.0
vals-excel-modeling	6.2	-0.0
automationbench	6.2	-0.0
gdp-pdf	6.2	+0.0
livebench-math	6.2	+0.0
swe-atlas-refactoring	6.2	-0.0
livebench-data	6.2	-0.0
frontiermath	6.2	+0.0
swe-bench-pro	6.2	+0.0

What evidence is missing from the fit?

Across all collected settings for this model: 79 observations, 56 contributing, 0 matched without graph weight and 23 excluded. Counts do not establish rank eligibility.

3 · Benchmark family or source protocol has not been reviewed
1 · Original SciCode grading defects are under review; retained as supporting evidence, excluded from aggregate and capability scores. Corrected SciCode-Verified requires a separate protocol review. Sources: https://arxiv.org/abs/2608.04975 and https://artificialanalysis.ai/evaluations/scicode
12 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately
7 · Supporting evidence outside the reviewed capability core

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 / source	Minimal	Low	Medium	High
AA-Briefcase EloArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details AA-Briefcase v1.1 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 2026-10-18.	Not reported	Not reported	Not reported	428.44 Elo Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
AIME 2025Artificial 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 2026-10-18.	46.67% Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	85% Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	90.67% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	39.33% Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	72.33% Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	72.33% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	Not reported	Not reported	Not reported	6.49% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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.	0% Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	1.43% Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	0% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
GDP.pdf: All-pass RateArtificial 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 2026-10-18.	Not reported	Not reported	Not reported	8.4% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
GDPval-AA v2.1 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 DeepSeek V4.1 Flash (max) at 1600 · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-10-18.	Not reported	Not reported	Not reported	766.11 Elo Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
Global-MMLU-LiteArtificial 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 2026-10-18.	Not reported	Not reported	Not reported	87.43% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	68.69% Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	80.3% Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	82.83% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	5.05% Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	15.94% Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	21.46% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	45.58% Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	71.16% Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	75.44% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	54.5% Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	69.21% Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	83.81% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	77.45% Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	82.78% Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	83.73% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
MMMU-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 2026-10-18.	58.38% Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	68.84% Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	70.06% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	-53.05 Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	-11.03 Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	-17.32 Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	19.17% Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	23.07% Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	24.97% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
SciCodeArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Benchmark curated by scientists across 16 disciplines. SciCode is under review following an independent audit of the dataset · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	Not reported	39% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	31.87% Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	71.05% Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	68.42% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	Not reported	Not reported	Not reported	15.46% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	14.39% Reported settings GPT-5 mini (Minimal); Model source: https://artificialanalysis.ai/models/gpt-5-mini-minimal	Not reported	28.79% Reported settings GPT-5 mini (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-mini-medium	33.33% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	Not reported	Not reported	Not reported	3.75% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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 2026-10-18.	Not reported	Not reported	Not reported	0% Reported settings GPT-5 mini (High); Model source: https://artificialanalysis.ai/models/gpt-5-mini
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.	1.67% Reported settings GPT-5 Mini (Minimal); Source model ID: gpt-5-mini-2025-08-07-minimal; 120 tasks	0.83% Reported settings GPT-5 Mini (Low); Source model ID: gpt-5-mini-2025-08-07-low; 120 tasks	4.03% Reported settings GPT-5 Mini (Medium); Source model ID: gpt-5-mini-2025-08-07-medium; 120 tasks	4.44% Reported settings GPT-5 Mini (High); Source model ID: gpt-5-mini-2025-08-07-high; 120 tasks
SWE-rebench · 2025-08 · toolsSWE-rebench · SWE-rebench standardized ReAct tools Benchmark details Average resolved rate across repeated runs, not best-of-N success. Disjoint complete calendar months within each model’s tested range; standardized harness and all-language task set. Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	43.08% Reported settings SWE-rebench standardized ReAct tools; swe-rebench-2025-08-tools; gpt-5-mini-2025-08-07-medium; checkpoint=gpt-5-mini	Not reported
SWE-rebench · 2025-09 · toolsSWE-rebench · SWE-rebench standardized ReAct tools Benchmark details Average resolved rate across repeated runs, not best-of-N success. Disjoint complete calendar months within each model’s tested range; standardized harness and all-language task set. Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	37.14% Reported settings SWE-rebench standardized ReAct tools; swe-rebench-2025-09-tools; gpt-5-mini-2025-08-07-medium; checkpoint=gpt-5-mini	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 · 8,915 results across 259 models · Collected 2026-10-18

GPT-5 Mini · High

Compare with

One configuration, seven capabilities

Agentic

Hard reasoning

Coding

Human pref

Knowledge

Multimodal

Long context

Capability score evidence

Benchmark results