RankingEffort benchmarks

GPT-5.4 Nano · XHigh

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79 measured results · 5 effort settings · 55 benchmark/harness combinations

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Capability profile

One configuration, seven capabilities

Comparison score · 0–100

AGPT-5.4 Nano · XHigh4 of 7 capabilities supported

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

Agentic
A31.3Supported
Hard reasoning
A23.8Supported
Coding
A25.5Supported
Human pref
Unknown
Knowledge
A21.6Supported
Multimodal
A8.0Preliminary
Long context
A24.5Preliminary

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-5.4 Nano · XHigh: 11.9 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 · 40.1% direct comparison weight · independent of the model provider
ARC Prize · 32.8% direct comparison weight · independent of the model provider
LiveBench · 27.1% direct comparison weight · independent of the model provider

Which benchmark families carry the weight?

ARC-AGI · 32.8% direct comparison weight
livebench-coding · 3.9% direct comparison weight
livebench-data · 3.9% direct comparison weight
livebench-language · 3.9% direct comparison weight
multi-swe-bench · 3.9% direct comparison weight
Other families (19) · 51.7% 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	141 → 138	Up 3	203 remaining / 241 lost	12.0 (+0.1 points)
ARC Prize	178 → 161	Up 17	444 remaining / 0 lost	18.4 (+6.5 points)
Datacurve	178 → 178	No movement	444 remaining / 0 lost	9.6 (-2.3 points)
LiveCodeBench	178 → 178	No movement	444 remaining / 0 lost	11.9 (-0.0 points)
Scale	178 → 178	No movement	444 remaining / 0 lost	13.5 (+1.6 points)
Terminal-Bench	178 → 178	No movement	444 remaining / 0 lost	11.9 (-0.0 points)
Cognition	178 → 178	No movement	444 remaining / 0 lost	11.9 (-0.0 points)
LiveBench	177 → 209	Down 32	443 remaining / 1 lost	9.1 (-2.8 points)
SWE-rebench	178 → 181	Down 3	444 remaining / 0 lost	11.9 (+0.0 points)
Epoch AI	174 → 176	Down 2	431 remaining / 13 lost	12.3 (+0.4 points)
Vals AI	178 → 178	No movement	443 remaining / 1 lost	11.5 (-0.4 points)
Provider reports · Anthropic	178 → 178	No movement	444 remaining / 0 lost	11.9 (-0.0 points)
Provider reports · Moonshot AI	178 → 178	No movement	444 remaining / 0 lost	11.6 (-0.3 points)
Provider reports · Meta	178 → 178	No movement	444 remaining / 0 lost	11.9 (-0.0 points)
Provider reports · Mistral	178 → 178	No movement	444 remaining / 0 lost	11.9 (+0.0 points)
Provider reports · OpenAI	178 → 178	No movement	444 remaining / 0 lost	12.0 (+0.1 points)
All provider reports	178 → 178	No movement	444 remaining / 0 lost	11.7 (-0.2 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	17.7	+5.8
deepswe	9.6	-2.3
mmmu-pro	13.1	+1.2
livebench-language	12.7	+0.8
hle	12.6	+0.7
livebench-coding	12.5	+0.6
livebench-data	11.4	-0.5
ifbench	11.4	-0.5
simpleqa	12.4	+0.5
epoch-game-puzzles	11.4	-0.5
arc-agi-3	11.5	-0.4
multi-swe-bench	11.6	-0.3
mmlu-pro	12.2	+0.3
livebench-instructions	11.6	-0.3
livebench-math	11.7	-0.2
itbench	12.1	+0.2
apex-agents	11.7	-0.2
critpt	11.7	-0.2
harvey	11.8	-0.1
gdp-pdf	12.0	+0.1
tau-bench	11.8	-0.1
aa-lcr	11.8	-0.1
swe-atlas-qna	11.8	-0.1
enigma-eval	11.8	-0.1
aime	11.8	-0.1
briefcase	12.0	+0.1
automationbench	12.0	+0.1
terminal-bench-science	12.0	+0.1
vibe-code	11.8	-0.1
omniscience	11.8	-0.1
enterprise-ops	12.0	+0.1
vals-finance-agent	11.8	-0.1
gpqa	11.8	-0.1
swe-atlas-test-writing	11.8	-0.0
analyst-agent	11.9	+0.0
livebench-reasoning	11.9	-0.0
terminal-bench	11.9	-0.0
frontiermath	11.9	+0.0
swe-rebench	11.9	+0.0
vals-legal-research	11.9	-0.0
vals-code-migration	11.9	-0.0
vals-tax-agent	11.9	-0.0
frontiercode	11.9	-0.0
vals-excel-modeling	11.9	-0.0
math500	11.9	+0.0
livecodebench	11.9	-0.0
swe-atlas-refactoring	11.9	-0.0
gdpval	11.9	+0.0
gmmlu	11.9	+0.0
swe-bench-pro	11.9	+0.0

What evidence is missing from the fit?

Across all collected settings for this model: 80 observations, 75 contributing, 0 matched without graph weight and 5 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
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 / source	Low	Medium	High	XHigh	Non-reasoning
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	673.76 Elo Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	Not reported
APEX-Agents-AAArtificial 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	24.93% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	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 2026-10-18.	Not reported	67.33% Reported settings GPT-5.4 nano (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-medium	Not reported	76.67% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	29.67% Reported settings GPT-5.4 nano (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-non-reasoning
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	5.96% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	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. 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	5.14% Reported settings GPT-5.4 nano (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-medium	Not reported	9.25% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	0% Reported settings GPT-5.4 nano (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-non-reasoning
EnterpriseOps-Gym-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Overall task success rate across all eight enterprise domains (oracle tool mode) · Benchmark developed by ServiceNow 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	31.48% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	Not reported
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	7.8% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	Not reported
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	947.98 Elo Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	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 2026-10-18.	Not reported	76.06% Reported settings GPT-5.4 nano (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-medium	Not reported	81.72% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	55.76% Reported settings GPT-5.4 nano (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-non-reasoning
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.	Not reported	15.94% Reported settings GPT-5.4 nano (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-medium	Not reported	28.27% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	4.08% Reported settings GPT-5.4 nano (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-non-reasoning
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.	Not reported	64.42% Reported settings GPT-5.4 nano (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-medium	Not reported	75.92% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	32.72% Reported settings GPT-5.4 nano (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-non-reasoning
ITBench-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Combined public and private Site Reliability Engineering (SRE) tasks · 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	24.39% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	12.91% Reported settings GPT-5.4 nano (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-non-reasoning
MLCR-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Share of tasks judged accurate, complete, and concise · Expert + compound (hard) sets · Benchmark developed by Wisedocs · 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	5% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	Not reported
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.	Not reported	59.54% Reported settings GPT-5.4 nano (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-medium	Not reported	65.38% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	43.76% Reported settings GPT-5.4 nano (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-non-reasoning
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.	Not reported	-18.03 Reported settings GPT-5.4 nano (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-medium	Not reported	-29.47 Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	-37.48 Reported settings GPT-5.4 nano (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-non-reasoning
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.	Not reported	21.9% Reported settings GPT-5.4 nano (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-medium	Not reported	25.67% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	14.88% Reported settings GPT-5.4 nano (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-non-reasoning
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	47.22% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	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 2026-10-18.	Not reported	52.63% Reported settings GPT-5.4 nano (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-medium	Not reported	76.02% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	34.8% Reported settings GPT-5.4 nano (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-non-reasoning
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	27.42% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	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 2026-10-18.	Not reported	33.33% Reported settings GPT-5.4 nano (Medium); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-medium	Not reported	42.42% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	24.24% Reported settings GPT-5.4 nano (Non-reasoning); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano-non-reasoning
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	60.67% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	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 2026-10-18.	Not reported	Not reported	Not reported	0.51% Reported settings GPT-5.4 nano (Xhigh); Model source: https://artificialanalysis.ai/models/gpt-5-4-nano	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 2026-10-18.	1.53% Reported settings GPT-5.4 Nano (Low); Source model ID: gpt-5-4-nano-low; 120 tasks	1.94% Reported settings GPT-5.4 Nano (Medium); Source model ID: gpt-5-4-nano-medium; 120 tasks	3.61% Reported settings GPT-5.4 Nano (High); Source model ID: gpt-5-4-nano-high; 120 tasks	5.69% Reported settings GPT-5.4 Nano (XHigh); Source model ID: gpt-5-4-nano-xhigh; 120 tasks	Not reported
LiveBench · AMPS Hard · 2026-06-25LiveBench · LiveBench official task evaluation Benchmark details LiveBench 2026-06-25 task snapshot. Task scores stay separate and related tasks share their reviewed family budget. Explicit checkpoint and effort labels only. Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	Not reported	98% Reported settings LiveBench official task evaluation; livebench-2026-06-25-AMPS_Hard; gpt-5.4-nano-xhigh; checkpoint=gpt-5.4-nano	Not reported
LiveBench · code completion · 2026-06-25LiveBench · LiveBench official task evaluation Benchmark details LiveBench 2026-06-25 task snapshot. Task scores stay separate and related tasks share their reviewed family budget. Explicit checkpoint and effort labels only. Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	Not reported	67.39% Reported settings LiveBench official task evaluation; livebench-2026-06-25-code_completion; gpt-5.4-nano-xhigh; checkpoint=gpt-5.4-nano	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-5.4 Nano · XHigh

Compare with

One configuration, seven capabilities

Agentic

Hard reasoning

Coding

Human pref

Knowledge

Multimodal

Long context

Capability score evidence

Benchmark results