GPT-5.4 nano
Unavailable in this round
Language modelDeprecated
GPT-5.4 nano
OpenAI
- Released
- March 17, 2026
- Data date
- September 8, 2026
- Predecessor
- GPT-5 nano
- Benchmark-Meta-Score
- Standard error ± 0.3
- Speed
- 176.1 tokens/sOutput throughput
- Price
- Input · Output / 1M tokens
- Input
- Text, Image
- Output
- Text
GPT-5.4 nano is the GPT-5.4 family’s smallest API tier. OpenAI released it alongside GPT-5.4 mini as an update to GPT-5 nano. Nano targets classification, data extraction, and ranking, while mini also handles computer use.
GPT-5.4 nano was deprecated on October 1, 2026, with shutdown announced for April 1, 2027.
- Position
- Rank 62 of 91
- Index score
- 0.7 / 100
Methodology and source
The LLM comparison hub's selected-panel index averages rank percentiles from 65 documented comparison cohorts. Benchmark meta-scores are shown in the benchmark section.
Benchmark meta-analysis
Overall and area scores
These Gradually indexes place selected published measurements on a 0 to 100 scale. They are not accuracy percentages and do not guarantee results in your application.
Retrieval dates of the sources used 2026-10-15 - 2026-10-19
Overall index
Index below 1 / 100
provisional
Estimated without own results in: Mathematics
Published configurations differ within this comparison cohort. Treat the index as provisional.
- Standard error
- ± 0.3
- 95% interval
- 0.2 to 1.7
- Test series
- 33
- Test families
- 29 / 65
- Sources
- 2
- Share of the fixed test panel (informative)
- 43 %
Coding
Index 1.6 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
- Standard error
- ± 1.3
- 95% interval
- 0.3 to 6.3
- Test series
- 7
- Test families
- 5 / 15
- Sources
- 2
- Share of the fixed test panel (informative)
- 29 %
Reasoning
Index 2.1 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
- Standard error
- ± 1.4
- 95% interval
- 0.5 to 6.7
- Test series
- 4
- Test families
- 4 / 7
- Sources
- 2
- Share of the fixed test panel (informative)
- 43 %
Knowledge
Index below 1 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
- Standard error
- ± 0.0
- 95% interval
- 0.0 to 0.3
- Test series
- 2
- Test families
- 2 / 3
- Sources
- 2
- Share of the fixed test panel (informative)
- 67 %
Agents
Index 1.5 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
- Standard error
- ± 1.4
- 95% interval
- 0.2 to 7.7
- Test series
- 5
- Test families
- 5 / 12
- Sources
- 1
- Share of the fixed test panel (informative)
- 42 %
General
Index 5.5 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
- Standard error
- ± 2.2
- 95% interval
- 2.3 to 11.2
- Test series
- 1
- Test families
- 1 / 5
- Sources
- 1
- Share of the fixed test panel (informative)
- 20 %
Finance
Index below 1 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
- Standard error
- ± 0.8
- 95% interval
- 0.1 to 4.8
- Test series
- 6
- Test families
- 6 / 7
- Sources
- 1
- Share of the fixed test panel (informative)
- 86 %
Legal
Index below 1 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
- Standard error
- ± 0.1
- 95% interval
- 0.0 to 0.4
- Test series
- 3
- Test families
- 3 / 4
- Sources
- 1
- Share of the fixed test panel (informative)
- 75 %
Health
Index 2.6 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
- Standard error
- ± 1.0
- 95% interval
- 1.2 to 5.3
- Test series
- 2
- Test families
- 2 / 3
- Sources
- 1
- Share of the fixed test panel (informative)
- 67 %
Multimodal
Index below 1 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
- Standard error
- ± 0.1
- 95% interval
- 0.0 to 0.3
- Test series
- 2
- Test families
- 1 / 4
- Sources
- 2
- Share of the fixed test panel (informative)
- 25 %
Education
Index below 1 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
- Standard error
- ± 0.2
- 95% interval
- 0.1 to 1.0
- Test series
- 1
- Test families
- 1 / 2
- Sources
- 1
- Share of the fixed test panel (informative)
- 50 %
Documented method · Included test families and measurements
Method version: benchmark-meta-score-v3
The index includes active measurements from reviewed primary sources when at least five models are compared in the same documented comparison slice across dataset, harness, agent, tools, and trial count. Each benchmark series and evaluator contributes one shared setup slice from the newest capture. When one source and series include several explicitly documented reasoning tiers, the highest documented tier (none through max) is selected, never the best result value. The explicit source label “Non-reasoning” is treated as none. Unknown or ambiguous tiers exclude the model from that series. Within each series, percentages and rates are logit-transformed, other units stay unchanged, and all values are then standardized. A one-factor model then estimates one shared strength per model and, per series, how sharply it separates the models. Area scores move away from that strength only as far as the model's own results in the area support. The overall score weights the core areas at 75% and finance, law and health at 25%. It requires at least eight test series from two sources and three areas. The 0 to 100 scale refers to a fixed reference group of 29 language models whose average sits at 50.
Published model-specific parameters can differ. This is not a controlled experiment; comparisons with such differences are marked provisional.
Unmeasured series are not entered as zero. Where a model has no own results in a core area, its overall strength stands in, and the note “estimated without own results in …” names the area. Fewer test series lead to a larger standard error.
The 95% interval follows from the standard error of 200 recalculations with randomly redrawn test families. It describes how precisely the recorded test series determine the value. It is no prediction for future tasks or for later recalculations with other participants.
The source count is not a count of independent experiments.
OECD handbook on composite indicatorsAll 30 test families and 12 of 33 raw measurements are listed here. The complete calculation for every model is available in the JSON export.
Test family: AA-Briefcase
Agents · Mean rank percentile of the family: 35.4 / 100Family weight in the fixed test panel (informative): 0.89 % · Coverage of this test family: 100 %
- Artificial Analysis
Published configurations differ within this cohort.
- Measurement:
- artificial-analysis-aa-briefcase
- Series weight within the test family:
- 100 %
- Nominal contribution to the overall panel:
- 0.89 %
- Raw value:
- 673.76 Elo
- Metric:
- AA-Briefcase Elo
- Version:
- v1.1
- Participating models:
- 83
- Rank percentile within the cohort:
- 35.4 %
- Retrieved:
- 2026-10-19
- Comparison cohort:
- artificial-analysis-aa-briefcase:v1.1:v4.3.2:reasoning:tokens=0:suffix=Xhigh
- Reasoning tier:
- Xhigh
- Documented comparison setup
- Publication cohort:
- ["artificial-analysis-aa-briefcase","v1.1","aa-model-page-2026-10-19-8a022369738c"]
- Dataset type:
- artificial-analysis-evaluation
- Setup and model parameters
- Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Reasoning: reasoning enabled. Reasoning effort: Xhigh
Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Source model ID: artificial-analysis/d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31/gpt-5-4-nano/gpt-5-4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: GPT-5.4 nano (Xhigh). Evaluator: Artificial Analysis. Dataset type: artificial-analysis-evaluation. Reasoning: reasoning enabled. Reasoning effort: Xhigh. Source ID: artificial-analysis. Evidence capture ID: aa-model-page-2026-10-19-8a022369738c. Source payload hash: 8a022369738cbe2a0e2f9bf486a2882865dbb0c6f1396dfec84059a802560e3c. Parser version: artificial-analysis-rsc-models-v2. Imported at: 2026-10-19
- Artificial Analysis
Test family: AA-LCR
Reasoning · Mean rank percentile of the family: 44.5 / 100Family weight in the fixed test panel (informative): 1.53 % · Coverage of this test family: 100 %
- Artificial Analysis
Published configurations differ within this cohort.
- Measurement:
- artificial-analysis-aa-lcr
- Series weight within the test family:
- 100 %
- Nominal contribution to the overall panel:
- 1.53 %
- Raw value:
- 76.6666666666667 %
- Metric:
- Pass rate
- Version:
- v1.1
- Participating models:
- 83
- Rank percentile within the cohort:
- 44.5 %
- Retrieved:
- 2026-10-19
- Comparison cohort:
- artificial-analysis-aa-lcr:v1.1:v4.3.2:reasoning:tokens=0:suffix=Xhigh
- Reasoning tier:
- Xhigh
- Documented comparison setup
- Publication cohort:
- ["artificial-analysis-aa-lcr","v1.1","aa-model-page-2026-10-19-8a022369738c"]
- Dataset type:
- artificial-analysis-evaluation
- Setup and model parameters
- Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Reasoning: reasoning enabled. Reasoning effort: Xhigh
Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Source model ID: artificial-analysis/d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31/gpt-5-4-nano/gpt-5-4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: GPT-5.4 nano (Xhigh). Evaluator: Artificial Analysis. Dataset type: artificial-analysis-evaluation. Reasoning: reasoning enabled. Reasoning effort: Xhigh. Score display: 76.7%. Source ID: artificial-analysis. Evidence capture ID: aa-model-page-2026-10-19-8a022369738c. Source payload hash: 8a022369738cbe2a0e2f9bf486a2882865dbb0c6f1396dfec84059a802560e3c. Parser version: artificial-analysis-rsc-models-v2. Imported at: 2026-10-19
- Artificial Analysis
Test family: APEX-Agents-AA
Agents · Mean rank percentile of the family: 46.2 / 100Family weight in the fixed test panel (informative): 0.89 % · Coverage of this test family: 100 %
- Artificial Analysis
Published configurations differ within this cohort.
- Measurement:
- artificial-analysis-apex-agents-aa
- Series weight within the test family:
- 100 %
- Nominal contribution to the overall panel:
- 0.89 %
- Raw value:
- 24.9262536873156 %
- Metric:
- Pass@1 success rate
- Version:
- AA public cohort: 452 tasks
- Participating models:
- 27
- Rank percentile within the cohort:
- 46.2 %
- Retrieved:
- 2026-10-19
- Comparison cohort:
- artificial-analysis-apex-agents-aa:AA public cohort: 452 tasks:standalone:reasoning:tokens=0:suffix=Xhigh
- Reasoning tier:
- Xhigh
- Documented comparison setup
- Publication cohort:
- ["artificial-analysis-apex-agents-aa","AA public cohort: 452 tasks","aa-model-page-2026-10-19-8a022369738c"]
- Dataset type:
- artificial-analysis-evaluation
- Harness:
- Artificial Analysis Stirrup
- Agent:
- Stirrup agent
- Tool policy:
- 200-turn cap; MCP-backed workplace tools in Archipelago
- Attempts:
- pass@1, averaged over 3 repeats per task
- Setup and model parameters
- Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption. 452 tasks from the public 480-task release, with three repeats per task. A run passes only if every rubric criterion is satisfied; the leaderboard averages pass@1 across repeats.. Harness: Artificial Analysis Stirrup. Agent: Stirrup agent. Tool policy: 200-turn cap; MCP-backed workplace tools in Archipelago. Attempts: pass@1, averaged over 3 repeats per task. Reasoning: reasoning enabled. Reasoning effort: Xhigh
Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption. 452 tasks from the public 480-task release, with three repeats per task. A run passes only if every rubric criterion is satisfied; the leaderboard averages pass@1 across repeats.. Source model ID: artificial-analysis/d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31/gpt-5-4-nano/gpt-5-4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: GPT-5.4 nano (Xhigh). Evaluator: Artificial Analysis. Dataset type: artificial-analysis-evaluation. Harness: Artificial Analysis Stirrup. Agent: Stirrup agent. Tool policy: 200-turn cap; MCP-backed workplace tools in Archipelago. Attempts: pass@1, averaged over 3 repeats per task. Reasoning: reasoning enabled. Reasoning effort: Xhigh. Score display: 24.9%. Source ID: artificial-analysis. Evidence capture ID: aa-model-page-2026-10-19-8a022369738c. Source payload hash: 8a022369738cbe2a0e2f9bf486a2882865dbb0c6f1396dfec84059a802560e3c. Parser version: artificial-analysis-rsc-models-v2. Imported at: 2026-10-19
- Artificial Analysis
Test family: AutomationBench-AA
Agents · Mean rank percentile of the family: 36.6 / 100Family weight in the fixed test panel (informative): 0.89 % · Coverage of this test family: 100 %
- Artificial Analysis
Published configurations differ within this cohort.
- Measurement:
- artificial-analysis-automationbench-aa
- Series weight within the test family:
- 100 %
- Nominal contribution to the overall panel:
- 0.89 %
- Raw value:
- 5.9606130748688075 %
- Metric:
- Objectives completed without guardrail violations
- Version:
- unspecified
- Participating models:
- 83
- Rank percentile within the cohort:
- 36.6 %
- Retrieved:
- 2026-10-19
- Comparison cohort:
- artificial-analysis-automationbench-aa:unspecified:v4.3.2:reasoning:tokens=0:suffix=Xhigh
- Reasoning tier:
- Xhigh
- Documented comparison setup
- Publication cohort:
- ["artificial-analysis-automationbench-aa","unspecified","aa-model-page-2026-10-19-8a022369738c"]
- Dataset type:
- artificial-analysis-evaluation
- Setup and model parameters
- Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Reasoning: reasoning enabled. Reasoning effort: Xhigh
Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Source model ID: artificial-analysis/d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31/gpt-5-4-nano/gpt-5-4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: GPT-5.4 nano (Xhigh). Evaluator: Artificial Analysis. Dataset type: artificial-analysis-evaluation. Reasoning: reasoning enabled. Reasoning effort: Xhigh. Score display: 6.0%. Source ID: artificial-analysis. Evidence capture ID: aa-model-page-2026-10-19-8a022369738c. Source payload hash: 8a022369738cbe2a0e2f9bf486a2882865dbb0c6f1396dfec84059a802560e3c. Parser version: artificial-analysis-rsc-models-v2. Imported at: 2026-10-19
- Artificial Analysis
Test family: GDP.pdf
Reasoning · Mean rank percentile of the family: 37.2 / 100Family weight in the fixed test panel (informative): 1.53 % · Coverage of this test family: 100 %
- Artificial Analysis
Published configurations differ within this cohort.
- Measurement:
- artificial-analysis-gdp-pdf
- Series weight within the test family:
- 100 %
- Nominal contribution to the overall panel:
- 1.53 %
- Raw value:
- 7.8 %
- Metric:
- All-pass rate
- Version:
- unspecified
- Participating models:
- 83
- Rank percentile within the cohort:
- 37.2 %
- Retrieved:
- 2026-10-19
- Comparison cohort:
- artificial-analysis-gdp-pdf:unspecified:v4.3.2:reasoning:tokens=0:suffix=Xhigh
- Reasoning tier:
- Xhigh
- Documented comparison setup
- Publication cohort:
- ["artificial-analysis-gdp-pdf","unspecified","aa-model-page-2026-10-19-8a022369738c"]
- Dataset type:
- artificial-analysis-evaluation
- Setup and model parameters
- Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Reasoning: reasoning enabled. Reasoning effort: Xhigh
Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Source model ID: artificial-analysis/d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31/gpt-5-4-nano/gpt-5-4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: GPT-5.4 nano (Xhigh). Evaluator: Artificial Analysis. Dataset type: artificial-analysis-evaluation. Reasoning: reasoning enabled. Reasoning effort: Xhigh. Score display: 7.8%. Source ID: artificial-analysis. Evidence capture ID: aa-model-page-2026-10-19-8a022369738c. Source payload hash: 8a022369738cbe2a0e2f9bf486a2882865dbb0c6f1396dfec84059a802560e3c. Parser version: artificial-analysis-rsc-models-v2. Imported at: 2026-10-19
- Artificial Analysis
Test family: GDPval-AA
Agents · Mean rank percentile of the family: 40.2 / 100Family weight in the fixed test panel (informative): 0.89 % · Coverage of this test family: 100 %
- Artificial Analysis
Published configurations differ within this cohort.
- Measurement:
- artificial-analysis-gdpval-aa
- Series weight within the test family:
- 100 %
- Nominal contribution to the overall panel:
- 0.89 %
- Raw value:
- 947.98 Elo
- Metric:
- GDPval-AA Elo
- Version:
- v2.1
- Participating models:
- 83
- Rank percentile within the cohort:
- 40.2 %
- Retrieved:
- 2026-10-19
- Comparison cohort:
- artificial-analysis-gdpval-aa:v2.1:v4.3.2:reasoning:tokens=0:suffix=Xhigh
- Reasoning tier:
- Xhigh
- Documented comparison setup
- Publication cohort:
- ["artificial-analysis-gdpval-aa","v2.1","aa-model-page-2026-10-19-8a022369738c"]
- Dataset type:
- artificial-analysis-evaluation
- Setup and model parameters
- Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Reasoning: reasoning enabled. Reasoning effort: Xhigh
Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Source model ID: artificial-analysis/d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31/gpt-5-4-nano/gpt-5-4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: GPT-5.4 nano (Xhigh). Evaluator: Artificial Analysis. Dataset type: artificial-analysis-evaluation. Reasoning: reasoning enabled. Reasoning effort: Xhigh. Source ID: artificial-analysis. Evidence capture ID: aa-model-page-2026-10-19-8a022369738c. Source payload hash: 8a022369738cbe2a0e2f9bf486a2882865dbb0c6f1396dfec84059a802560e3c. Parser version: artificial-analysis-rsc-models-v2. Imported at: 2026-10-19
- Artificial Analysis
Test family: IFBench
General · Mean rank percentile of the family: 89.9 / 100Family weight in the fixed test panel (informative): 2.14 % · Coverage of this test family: 100 %
- Artificial Analysis
Published configurations differ within this cohort.
- Measurement:
- artificial-analysis-ifbench
- Series weight within the test family:
- 100 %
- Nominal contribution to the overall panel:
- 2.14 %
- Raw value:
- 75.9183673469388 %
- Metric:
- IFBench prompt-level loose accuracy (pass@1)
- Version:
- AA test set: 294 questions
- Participating models:
- 70
- Rank percentile within the cohort:
- 89.9 %
- Retrieved:
- 2026-10-19
- Comparison cohort:
- artificial-analysis-ifbench:AA test set: 294 questions:standalone:reasoning:tokens=0:suffix=Xhigh
- Reasoning tier:
- Xhigh
- Documented comparison setup
- Publication cohort:
- ["artificial-analysis-ifbench","AA test set: 294 questions","aa-model-page-2026-10-19-8a022369738c"]
- Dataset type:
- artificial-analysis-evaluation
- Tool policy:
- Single-turn answer evaluated with the official IFBench source code
- Attempts:
- pass@1, 5 repeats per question
- Setup and model parameters
- Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption. Artificial Analysis runs 294 questions from the IFBench test set with five repeats per question. The official evaluator scores prompt-level accuracy in loose mode as pass@1.. Tool policy: Single-turn answer evaluated with the official IFBench source code. Attempts: pass@1, 5 repeats per question. Reasoning: reasoning enabled. Reasoning effort: Xhigh
Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption. Artificial Analysis runs 294 questions from the IFBench test set with five repeats per question. The official evaluator scores prompt-level accuracy in loose mode as pass@1.. Source model ID: artificial-analysis/d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31/gpt-5-4-nano/gpt-5-4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: GPT-5.4 nano (Xhigh). Evaluator: Artificial Analysis. Dataset type: artificial-analysis-evaluation. Tool policy: Single-turn answer evaluated with the official IFBench source code. Attempts: pass@1, 5 repeats per question. Reasoning: reasoning enabled. Reasoning effort: Xhigh. Score display: 75.9%. Source ID: artificial-analysis. Evidence capture ID: aa-model-page-2026-10-19-8a022369738c. Source payload hash: 8a022369738cbe2a0e2f9bf486a2882865dbb0c6f1396dfec84059a802560e3c. Parser version: artificial-analysis-rsc-models-v2. Imported at: 2026-10-19
- Artificial Analysis
Test family: ITBench-AA (SRE)
Agents · Mean rank percentile of the family: 8.6 / 100Family weight in the fixed test panel (informative): 0.89 % · Coverage of this test family: 100 %
- Artificial Analysis
Published configurations differ within this cohort.
- Measurement:
- artificial-analysis-itbench-aa
- Series weight within the test family:
- 100 %
- Nominal contribution to the overall panel:
- 0.89 %
- Raw value:
- 24.3879472693032 %
- Metric:
- Average precision at full recall
- Version:
- AA cohort: 59 tasks
- Participating models:
- 36
- Rank percentile within the cohort:
- 8.6 %
- Retrieved:
- 2026-10-19
- Comparison cohort:
- artificial-analysis-itbench-aa:AA cohort: 59 tasks:standalone:reasoning:tokens=0:suffix=Xhigh
- Reasoning tier:
- Xhigh
- Documented comparison setup
- Publication cohort:
- ["artificial-analysis-itbench-aa","AA cohort: 59 tasks","aa-model-page-2026-10-19-8a022369738c"]
- Dataset type:
- artificial-analysis-evaluation
- Harness:
- Artificial Analysis Stirrup
- Agent:
- Stirrup agent
- Tool policy:
- Shell access to an offline Kubernetes incident snapshot
- Attempts:
- Average precision at full recall, 3 repeats per task
- Setup and model parameters
- Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption. 59 Kubernetes incident tasks, 40 public and 19 private, with three repeats per task. A run scores zero if it misses any true root cause; otherwise it receives its precision at full recall. This is the SRE slice of ITBench.. Harness: Artificial Analysis Stirrup. Agent: Stirrup agent. Tool policy: Shell access to an offline Kubernetes incident snapshot. Attempts: Average precision at full recall, 3 repeats per task. Reasoning: reasoning enabled. Reasoning effort: Xhigh
Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption. 59 Kubernetes incident tasks, 40 public and 19 private, with three repeats per task. A run scores zero if it misses any true root cause; otherwise it receives its precision at full recall. This is the SRE slice of ITBench.. Source model ID: artificial-analysis/d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31/gpt-5-4-nano/gpt-5-4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: GPT-5.4 nano (Xhigh). Evaluator: Artificial Analysis. Dataset type: artificial-analysis-evaluation. Harness: Artificial Analysis Stirrup. Agent: Stirrup agent. Tool policy: Shell access to an offline Kubernetes incident snapshot. Attempts: Average precision at full recall, 3 repeats per task. Reasoning: reasoning enabled. Reasoning effort: Xhigh. Score display: 24.4%. Source ID: artificial-analysis. Evidence capture ID: aa-model-page-2026-10-19-8a022369738c. Source payload hash: 8a022369738cbe2a0e2f9bf486a2882865dbb0c6f1396dfec84059a802560e3c. Parser version: artificial-analysis-rsc-models-v2. Imported at: 2026-10-19
- Artificial Analysis
Test family: AA-Omniscience
Knowledge · Mean rank percentile of the family: 28.0 / 100Family weight in the fixed test panel (informative): 3.57 % · Coverage of this test family: 100 %
- Artificial Analysis
Published configurations differ within this cohort.
- Measurement:
- artificial-analysis-omniscience
- Series weight within the test family:
- 100 %
- Nominal contribution to the overall panel:
- 3.57 %
- Raw value:
- -29.466666666666665 points
- Metric:
- AA-Omniscience Index
- Version:
- unspecified
- Participating models:
- 83
- Rank percentile within the cohort:
- 28.0 %
- Retrieved:
- 2026-10-19
- Comparison cohort:
- artificial-analysis-omniscience:unspecified:v4.3.2:reasoning:tokens=0:suffix=Xhigh
- Reasoning tier:
- Xhigh
- Documented comparison setup
- Publication cohort:
- ["artificial-analysis-omniscience","unspecified","aa-model-page-2026-10-19-8a022369738c"]
- Dataset type:
- artificial-analysis-evaluation
- Setup and model parameters
- Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Reasoning: reasoning enabled. Reasoning effort: Xhigh
Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Source model ID: artificial-analysis/d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31/gpt-5-4-nano/gpt-5-4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: GPT-5.4 nano (Xhigh). Evaluator: Artificial Analysis. Dataset type: artificial-analysis-evaluation. Reasoning: reasoning enabled. Reasoning effort: Xhigh. Source ID: artificial-analysis. Evidence capture ID: aa-model-page-2026-10-19-8a022369738c. Source payload hash: 8a022369738cbe2a0e2f9bf486a2882865dbb0c6f1396dfec84059a802560e3c. Parser version: artificial-analysis-rsc-models-v2. Imported at: 2026-10-19
- Artificial Analysis
Test family: GPQA Diamond
Reasoning · Mean rank percentile of the family: 28.9 / 100Family weight in the fixed test panel (informative): 1.53 % · Coverage of this test family: 50 %
- Vals AI
Published configurations differ within this cohort.
- Measurement:
- vals-gpqa
- Series weight within the test family:
- 50 %
- Nominal contribution to the overall panel:
- 0.77 %
- Raw value:
- 77.526 %
- Metric:
- accuracy
- Version:
- 1
- Participating models:
- 77
- Rank percentile within the cohort:
- 28.9 %
- Retrieved:
- 2026-10-15
- Comparison cohort:
- vals-gpqa:1:overall
- Reasoning tier:
- high
- Documented comparison setup
- Publication cohort:
- vals-gpqa:1:overall
- Dataset type:
- public
- Setup and model parameters
- Reasoning effort: high. Maximum output tokens: 128000
Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Reasoning effort: high. Maximum output tokens: 128000. Latency in seconds: 29.498. Standard error: 2.417. Cost per task in USD: 0.001565. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-10-15-951eb5224097. Source payload hash: 951eb5224097733a9d09d06c14908ae2980e2e640e539f2c284877c5092d7077. Parser version: vals-astro-v3. Imported at: 2026-10-15
- Vals AI
Test family: Humanity’s Last Exam
Reasoning · Mean rank percentile of the family: 39.0 / 100Family weight in the fixed test panel (informative): 1.53 % · Coverage of this test family: 50 %
- Artificial Analysis
Published configurations differ within this cohort.
- Measurement:
- artificial-analysis-humanitys-last-exam
- Series weight within the test family:
- 50 %
- Nominal contribution to the overall panel:
- 0.77 %
- Raw value:
- 28.2669138090825 %
- Metric:
- Text-only pass@1 accuracy
- Version:
- unspecified
- Participating models:
- 83
- Rank percentile within the cohort:
- 39.0 %
- Retrieved:
- 2026-10-19
- Comparison cohort:
- artificial-analysis-humanitys-last-exam:unspecified:v4.3.2:reasoning:tokens=0:suffix=Xhigh
- Reasoning tier:
- Xhigh
- Documented comparison setup
- Publication cohort:
- ["artificial-analysis-humanitys-last-exam","unspecified","aa-model-page-2026-10-19-8a022369738c"]
- Dataset type:
- artificial-analysis-evaluation
- Setup and model parameters
- Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Reasoning: reasoning enabled. Reasoning effort: Xhigh
Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption.. Source model ID: artificial-analysis/d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31/gpt-5-4-nano/gpt-5-4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: GPT-5.4 nano (Xhigh). Evaluator: Artificial Analysis. Dataset type: artificial-analysis-evaluation. Reasoning: reasoning enabled. Reasoning effort: Xhigh. Score display: 28.3%. Source ID: artificial-analysis. Evidence capture ID: aa-model-page-2026-10-19-8a022369738c. Source payload hash: 8a022369738cbe2a0e2f9bf486a2882865dbb0c6f1396dfec84059a802560e3c. Parser version: artificial-analysis-rsc-models-v2. Imported at: 2026-10-19
- Artificial Analysis
Test family: MMMU-Pro
Multimodal · Mean rank percentile of the family: 23.0 / 100Family weight in the fixed test panel (informative): 2.68 % · Coverage of this test family: 100 %
- Artificial Analysis
Published configurations differ within this cohort.
- Measurement:
- artificial-analysis-mmmu-pro
- Series weight within the test family:
- 50 %
- Nominal contribution to the overall panel:
- 1.34 %
- Raw value:
- 65.3757225433526 %
- Metric:
- pass@1 accuracy
- Version:
- AA cohort: 1,730 questions
- Participating models:
- 57
- Rank percentile within the cohort:
- 26.8 %
- Retrieved:
- 2026-10-19
- Comparison cohort:
- artificial-analysis-mmmu-pro:AA cohort: 1,730 questions:standalone:reasoning:tokens=0:suffix=Xhigh
- Reasoning tier:
- Xhigh
- Documented comparison setup
- Publication cohort:
- ["artificial-analysis-mmmu-pro","AA cohort: 1,730 questions","aa-model-page-2026-10-19-8a022369738c"]
- Dataset type:
- artificial-analysis-evaluation
- Tool policy:
- Ten-option multiple choice; regex answer extraction
- Attempts:
- pass@1, one run per question
- Setup and model parameters
- Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption. The AA run covers 1,730 questions with ten answer options. Answers are extracted by regex and scored pass@1.. Tool policy: Ten-option multiple choice; regex answer extraction. Attempts: pass@1, one run per question. Reasoning: reasoning enabled. Reasoning effort: Xhigh
Exact AA configuration: GPT-5.4 nano (Xhigh) (release gpt-5-4-nano, row gpt-5-4-nano, UUID d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31, reasoning=true, source reasoning-token configuration budget=0, suffix=Xhigh). This configured value is not measured token consumption. The AA run covers 1,730 questions with ten answer options. Answers are extracted by regex and scored pass@1.. Source model ID: artificial-analysis/d4fc3f33-f2b0-4da1-88ee-f1f82bd4de31/gpt-5-4-nano/gpt-5-4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: GPT-5.4 nano (Xhigh). Evaluator: Artificial Analysis. Dataset type: artificial-analysis-evaluation. Tool policy: Ten-option multiple choice; regex answer extraction. Attempts: pass@1, one run per question. Reasoning: reasoning enabled. Reasoning effort: Xhigh. Score display: 65.4%. Source ID: artificial-analysis. Evidence capture ID: aa-model-page-2026-10-19-8a022369738c. Source payload hash: 8a022369738cbe2a0e2f9bf486a2882865dbb0c6f1396dfec84059a802560e3c. Parser version: artificial-analysis-rsc-models-v2. Imported at: 2026-10-19
- Artificial Analysis
Test family: SWE-bench Verified
Coding · Mean rank percentile of the family: 23.7 / 100Family weight in the fixed test panel (informative): 0.71 % · Coverage of this test family: 50 %
Test family: Terminal-Bench
Coding · Mean rank percentile of the family: 35.0 / 100Family weight in the fixed test panel (informative): 0.71 % · Coverage of this test family: 83 %
Test family: Code Migration
Coding · Mean rank percentile of the family: 30.6 / 100Family weight in the fixed test panel (informative): 0.71 % · Coverage of this test family: 100 %
Test family: CorpFin v2
Finance · Mean rank percentile of the family: 49.3 / 100Family weight in the fixed test panel (informative): 1.19 % · Coverage of this test family: 100 %
Test family: EMB
Finance · Mean rank percentile of the family: 23.7 / 100Family weight in the fixed test panel (informative): 1.19 % · Coverage of this test family: 100 %
Test family: Finance Agent (v2)
Finance · Mean rank percentile of the family: 18.3 / 100Family weight in the fixed test panel (informative): 1.19 % · Coverage of this test family: 100 %
Test family: LiveCodeBench v6
Coding · Mean rank percentile of the family: 62.3 / 100Family weight in the fixed test panel (informative): 0.71 % · Coverage of this test family: 100 %
Test family: Harvey's Legal Agent Benchmark
Legal · Mean rank percentile of the family: 10.7 / 100Family weight in the fixed test panel (informative): 2.08 % · Coverage of this test family: 100 %
Test family: LegalBench
Legal · Mean rank percentile of the family: 21.8 / 100Family weight in the fixed test panel (informative): 2.08 % · Coverage of this test family: 100 %
Test family: Legal Research Bench
Legal · Mean rank percentile of the family: 6.7 / 100Family weight in the fixed test panel (informative): 2.08 % · Coverage of this test family: 100 %
Test family: MedCode
Health · Mean rank percentile of the family: 37.3 / 100Family weight in the fixed test panel (informative): 2.78 % · Coverage of this test family: 100 %
Test family: MedScribe
Health · Mean rank percentile of the family: 32.4 / 100Family weight in the fixed test panel (informative): 2.78 % · Coverage of this test family: 100 %
Test family: MMLU-Pro
Knowledge · Mean rank percentile of the family: 14.3 / 100Family weight in the fixed test panel (informative): 3.57 % · Coverage of this test family: 100 %
Test family: MortgageTax
Finance · Mean rank percentile of the family: 15.4 / 100Family weight in the fixed test panel (informative): 1.19 % · Coverage of this test family: 100 %
Test family: SAGE
Education · Mean rank percentile of the family: 20.7 / 100Family weight in the fixed test panel (informative): 0 % · Coverage of this test family: 100 %
Test family: Tax Agent Bench
Finance · Mean rank percentile of the family: 7.3 / 100Family weight in the fixed test panel (informative): 1.19 % · Coverage of this test family: 100 %
Test family: TaxEval v2
Finance · Mean rank percentile of the family: 14.5 / 100Family weight in the fixed test panel (informative): 1.19 % · Coverage of this test family: 100 %
Test family: Vibe Code Bench v1.1
Coding · Mean rank percentile of the family: 29.2 / 100Family weight in the fixed test panel (informative): 0.71 % · Coverage of this test family: 100 %
Benchmark sources at a glance
Each evaluator measures different capabilities under its own conditions. Test series, composite indices and their components stay separate. The detailed results below retain their scales, configurations and source dates.
| Evaluator | Test series | Composite indices | Recorded active measurements |
|---|---|---|---|
| Artificial Analysis | 12 | 1 | 31 |
| Vals AI | 23 | 2 | 182 |
Coverage is not a quality ranking. Overlapping tests and multiple settings do not count as independent experiments. Vendor claims, historical and disputed results are excluded from this overview and remain labelled in the detailed evidence.
7 measurements from these sources still lack a verified test-family identity and do not increase the test-series count.
Page 1 of 20
Published benchmarks
Taste-Bench
Overall
502 technical decision points from engineering and research workflows. Each choice is presented in both answer orders. The overall score averages engineering and research and requires both answer orders to be correct. Unparseable responses count as wrong. Reasoning settings and output budget are part of the setup.
Note (GPT-5.4 nano): 93 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
1.GPT-5.6 Sol59.7%
Note: 0 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
2.GPT-5.559.5%
Note: 0 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
3.Claude Opus 555.5%
Note: 0 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
4.Grok 4.554.6%
Note: 10 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
5.GPT-5.6 Terra54%
Note: 0 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
6.GLM-5.253.9%
Note: 17 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
7.Claude Sonnet 551.6%
Note: 0 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
8.GPT-5.6 Luna49%
Note: 0 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
9.MiniMax M345.3%
Note: 3 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
10.DeepSeek-V4-Flash43.3%
Note: 2 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
11.GPT-5.4 mini40.1%
Note: 112 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
12.Mistral Medium 3.537.7%
Note: 24 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
14.Grok 4.20 Reasoning15.7%
Note: 459 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
higher is betterAs of September 26, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- taste-bench-paper-v2-502
- Metric
- both-orders-correct, engineering/research macro average
- Scale
- 0-100
- Participants
- 14
- Methodology and context
- Same prompt for all models. Each of 502 questions is shown twice with the options reversed. Average of engineering and research success rates, requiring both orders to be correct. 65,536-token output budget; unparseable answers count as wrong.. Source model ID: curated/gpt-5.4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Evaluator: Taste-Bench paper. Dataset type: public. Leaderboard date: 2026-09-23. Attempts: 502 questions, two option orders each. Reasoning effort: high. Maximum output tokens: 65536. Source ID: taste-bench-paper. Evidence capture ID: curated-taste-bench-paper-2026-09-26-ee1a62d2083b. Source payload hash: ee1a62d2083b8b1184c46ee9fe59fc02bd5b2f0a63b87dbef0c3f163690c0542. Parser version: curated-v1. Imported at: 2026-10-15
Finance
CorpFin v2
| Sub-task | GPT-5.4 nano (This model) | GPT-5 mini |
|---|---|---|
| Exact Pages | 60.37% (best value in this row) | 58.86% |
| Max Fitting Context | 62.12% (best value in this row) | 60.49% |
| Overall | 61.19% (best value in this row) | 60.18% |
| Shared Max Context | 61.07% | 61.19% (best value in this row) |
higher is betterAs of October 15, 2026Source: Vals AIbars scaled within each row, not across rows
Methodology and context
- Metric
- accuracy
Health
MedCode
Overall
higher is betterAs of October 15, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-medcode:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 6
- Methodology and context
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-10-13. Reasoning effort: high. Maximum output tokens: 30000. Latency in seconds: 8.043. Standard error: 2.256. Cost per task in USD: 0.000844. Source ID: vals-ai. Evidence capture ID: vals-medcode-2026-10-15-988a6ae1e07e. Source payload hash: 988a6ae1e07e33ce031572ed4a804be11c36ee97a1dd75cbe4740fff3b534f8c. Parser version: vals-astro-v3. Imported at: 2026-10-15
MedScribe
Overall
higher is betterAs of October 15, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-medscribe:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 6
- Methodology and context
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-10-13. Reasoning effort: high. Maximum output tokens: 30000. Latency in seconds: 20.527. Standard error: 1.891. Cost per task in USD: 0.0018. Source ID: vals-ai. Evidence capture ID: vals-medscribe-2026-10-15-271fc122ddc2. Source payload hash: 271fc122ddc2b0602bd6c7947f65a9a7f0d8cab94f6dc27d62a9380a9317f9c0. Parser version: vals-astro-v3. Imported at: 2026-10-15
Education
SAGE
| Sub-task | GPT-5.4 nano (This model) | o4-mini | o3 | DeepSeek-V4.1-Flash | GPT-5 | GPT-5 mini | GPT-5 nano |
|---|---|---|---|---|---|---|---|
| Automata | 23.41% | 37.3% (best value in this row) | 36.91% | 32.94% | 29.76% | 29.76% | 5.16% |
| Calculus | 20.99% | 33.33% | 55.56% | 33.33% | 62.96% (best value in this row) | 39.82% | 7.72% |
| Linear Algebra | 60.67% | 54.14% | 61.42% | 62.29% | 61.6% | 62.7% (best value in this row) | 55.81% |
| Overall | 38.08% | 41.06% | 41.77% | 47.88% (best value in this row) | 43.68% | 42.99% | 30.38% |
| Partial Differential Equations | 30.16% | 31.75% | 26.98% | 48.41% (best value in this row) | 39.68% | 36.51% | 30.16% |
higher is betterAs of October 15, 2026Source: Vals AIbars scaled within each row, not across rows
Methodology and context
- Metric
- accuracy
Recorded measurement details
Taste-Bench: Overall (Show measurement, test conditions, and source)
- Source value
- 36.6
- Score
- 36.6
- Metric
- both-orders-correct, engineering/research macro average
- Unit
- %
- Benchmark version
- arxiv:2609.25804v2
- Category
- agentic
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- taste-bench-paper-v2-502
- Source type
- independent-evaluator
- Evaluator
- Taste-Bench paper
- Status
- active
- Retrieved at
- 2026-09-26
- Methodology
- Same prompt for all models. Each of 502 questions is shown twice with the options reversed. Average of engineering and research success rates, requiring both orders to be correct. 65,536-token output budget; unparseable answers count as wrong.. Source model ID: curated/gpt-5.4-nano. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Evaluator: Taste-Bench paper. Dataset type: public. Leaderboard date: 2026-09-23. Attempts: 502 questions, two option orders each. Reasoning effort: high. Maximum output tokens: 65536. Source ID: taste-bench-paper. Evidence capture ID: curated-taste-bench-paper-2026-09-26-ee1a62d2083b. Source payload hash: ee1a62d2083b8b1184c46ee9fe59fc02bd5b2f0a63b87dbef0c3f163690c0542. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- Same prompt for all models. Each of 502 questions is shown twice with the options reversed. Average of engineering and research success rates, requiring both orders to be correct. 65,536-token output budget; unparseable answers count as wrong.
- Context
- 93 of 1,004 responses were unparseable and counted as wrong. Not a Gradually test.
CorpFin v2: Exact Pages (Show measurement, test conditions, and source)
- Source value
- 60.373
- Score
- 60.373
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 2
- Category
- finance
- Task
- exact_pages
- Task label
- Exact Pages
- Direction
- Higher is better
- Comparison cohort
- vals-corp-fin-v2:2:exact_pages
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-12. Reasoning effort: high. Maximum output tokens: 128000. Latency in seconds: 8.67. Standard error: 1.67. Cost per task in USD: 0.000735. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-10-15-7cf2217ab372. Source payload hash: 7cf2217ab3728d5a84bffce82aab9fc52d7f810b0cbe8c65b387df47f3d31c9b. Parser version: vals-astro-v3. Imported at: 2026-10-15
- Comparison methodology
- Reasoning effort: high. Maximum output tokens: 128000
CorpFin v2: Max Fitting Context (Show measurement, test conditions, and source)
- Source value
- 62.121
- Score
- 62.121
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 2
- Category
- finance
- Task
- max_fitting_context
- Task label
- Max Fitting Context
- Direction
- Higher is better
- Comparison cohort
- vals-corp-fin-v2:2:max_fitting_context
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-12. Reasoning effort: high. Maximum output tokens: 128000. Latency in seconds: 12.158. Standard error: 1.656. Cost per task in USD: 0.035271. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-10-15-7cf2217ab372. Source payload hash: 7cf2217ab3728d5a84bffce82aab9fc52d7f810b0cbe8c65b387df47f3d31c9b. Parser version: vals-astro-v3. Imported at: 2026-10-15
- Comparison methodology
- Reasoning effort: high. Maximum output tokens: 128000
CorpFin v2: Overall (Show measurement, test conditions, and source)
- Source value
- 61.189
- Score
- 61.189
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 2
- Category
- finance
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-corp-fin-v2:2:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-12. Reasoning effort: high. Maximum output tokens: 128000. Latency in seconds: 9.397. Standard error: 0.961. Cost per task in USD: 0.01612. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-10-15-7cf2217ab372. Source payload hash: 7cf2217ab3728d5a84bffce82aab9fc52d7f810b0cbe8c65b387df47f3d31c9b. Parser version: vals-astro-v3. Imported at: 2026-10-15
- Comparison methodology
- Reasoning effort: high. Maximum output tokens: 128000
CorpFin v2: Shared Max Context (Show measurement, test conditions, and source)
- Source value
- 61.072
- Score
- 61.072
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 2
- Category
- finance
- Task
- shared_max_context
- Task label
- Shared Max Context
- Direction
- Higher is better
- Comparison cohort
- vals-corp-fin-v2:2:shared_max_context
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-12. Reasoning effort: high. Maximum output tokens: 128000. Latency in seconds: 7.363. Standard error: 1.665. Cost per task in USD: 0.012353. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-10-15-7cf2217ab372. Source payload hash: 7cf2217ab3728d5a84bffce82aab9fc52d7f810b0cbe8c65b387df47f3d31c9b. Parser version: vals-astro-v3. Imported at: 2026-10-15
- Comparison methodology
- Reasoning effort: high. Maximum output tokens: 128000
MedCode: Overall (Show measurement, test conditions, and source)
- Source value
- 41.029
- Score
- 41.029
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- health
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-medcode:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-10-13. Reasoning effort: high. Maximum output tokens: 30000. Latency in seconds: 8.043. Standard error: 2.256. Cost per task in USD: 0.000844. Source ID: vals-ai. Evidence capture ID: vals-medcode-2026-10-15-988a6ae1e07e. Source payload hash: 988a6ae1e07e33ce031572ed4a804be11c36ee97a1dd75cbe4740fff3b534f8c. Parser version: vals-astro-v3. Imported at: 2026-10-15
- Comparison methodology
- Reasoning effort: high. Maximum output tokens: 30000
MedScribe: Overall (Show measurement, test conditions, and source)
- Source value
- 77.09
- Score
- 77.09
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- health
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-medscribe:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-10-13. Reasoning effort: high. Maximum output tokens: 30000. Latency in seconds: 20.527. Standard error: 1.891. Cost per task in USD: 0.0018. Source ID: vals-ai. Evidence capture ID: vals-medscribe-2026-10-15-271fc122ddc2. Source payload hash: 271fc122ddc2b0602bd6c7947f65a9a7f0d8cab94f6dc27d62a9380a9317f9c0. Parser version: vals-astro-v3. Imported at: 2026-10-15
- Comparison methodology
- Reasoning effort: high. Maximum output tokens: 30000
SAGE: Automata (Show measurement, test conditions, and source)
- Source value
- 23.412
- Score
- 23.412
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- education
- Task
- automata
- Task label
- Automata
- Direction
- Higher is better
- Comparison cohort
- vals-sage:1:automata
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-10-08. Reasoning effort: high. Maximum output tokens: 30000. Latency in seconds: 38.242. Standard error: 4.736. Cost per task in USD: 0.004953. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-10-15-cc5fb3fecdb0. Source payload hash: cc5fb3fecdb0382d492ff167a42ad84b9c5c3883373c78ed87baaa972b8b6f7c. Parser version: vals-astro-v3. Imported at: 2026-10-15
- Comparison methodology
- Reasoning effort: high. Maximum output tokens: 30000
SAGE: Calculus (Show measurement, test conditions, and source)
- Source value
- 20.988
- Score
- 20.988
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- education
- Task
- calculus
- Task label
- Calculus
- Direction
- Higher is better
- Comparison cohort
- vals-sage:1:calculus
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-10-08. Reasoning effort: high. Maximum output tokens: 30000. Latency in seconds: 45.07. Standard error: 4.183. Cost per task in USD: 0.002745. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-10-15-cc5fb3fecdb0. Source payload hash: cc5fb3fecdb0382d492ff167a42ad84b9c5c3883373c78ed87baaa972b8b6f7c. Parser version: vals-astro-v3. Imported at: 2026-10-15
- Comparison methodology
- Reasoning effort: high. Maximum output tokens: 30000
SAGE: Linear Algebra (Show measurement, test conditions, and source)
- Source value
- 60.671
- Score
- 60.671
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- education
- Task
- linear_algebra
- Task label
- Linear Algebra
- Direction
- Higher is better
- Comparison cohort
- vals-sage:1:linear_algebra
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-10-08. Reasoning effort: high. Maximum output tokens: 30000. Latency in seconds: 26.941. Standard error: 5.477. Cost per task in USD: 0.005836. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-10-15-cc5fb3fecdb0. Source payload hash: cc5fb3fecdb0382d492ff167a42ad84b9c5c3883373c78ed87baaa972b8b6f7c. Parser version: vals-astro-v3. Imported at: 2026-10-15
- Comparison methodology
- Reasoning effort: high. Maximum output tokens: 30000
SAGE: Overall (Show measurement, test conditions, and source)
- Source value
- 38.081
- Score
- 38.081
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- education
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-sage:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-10-08. Reasoning effort: high. Maximum output tokens: 30000. Latency in seconds: 34.334. Standard error: 3.087. Cost per task in USD: 0.005936. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-10-15-cc5fb3fecdb0. Source payload hash: cc5fb3fecdb0382d492ff167a42ad84b9c5c3883373c78ed87baaa972b8b6f7c. Parser version: vals-astro-v3. Imported at: 2026-10-15
- Comparison methodology
- Reasoning effort: high. Maximum output tokens: 30000
SAGE: Partial Differential Equations (Show measurement, test conditions, and source)
- Source value
- 30.159
- Score
- 30.159
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- education
- Task
- PDEs
- Task label
- Partial Differential Equations
- Direction
- Higher is better
- Comparison cohort
- vals-sage:1:PDEs
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Provider reported by source: OpenAI. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-10-08. Reasoning effort: high. Maximum output tokens: 30000. Latency in seconds: 37.818. Standard error: 5.772. Cost per task in USD: 0.007019. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-10-15-cc5fb3fecdb0. Source payload hash: cc5fb3fecdb0382d492ff167a42ad84b9c5c3883373c78ed87baaa972b8b6f7c. Parser version: vals-astro-v3. Imported at: 2026-10-15
- Comparison methodology
- Reasoning effort: high. Maximum output tokens: 30000
Page 1 of 20
Our tests
SVG short test
One SVG prompt and fixed output settings. Captures are shown only with 0 reported reasoning tokens or documented lack of reasoning controls. Identical test conditions do not make the models' internal compute identical.
Earlier tests
Pelican on a bicycle
A community classic for free-form SVG drawing.
GPT-5.4 nano
Reasoning (requested): high
Current attempt
- Run date
- Oct 1, 2026
- API provider
- openrouter
- Requested API model
- openai/gpt-5.4-nano
- API model reported in response
- openai/gpt-5.4-nano
- Reasoning setting
- high
- Pinned endpoint
- OpenAI | openai/gpt-5.4-nano-20260317
- Temperature
- Provider default
- Token limit including reasoning
- 8,192 tokens
- Test protocol
- community-visual-tests-v1
- Technical checks
- Passed, not a quality rating
- Response time
- 21.6 s
Visually reviewed. This individual test does not establish overall model quality.
Prompt and test conditions
Generate an SVG of a pelican riding a bicycle
Token limit including reasoning: 8,192 tokens
Task origin (Simon Willison)Popularity
40.6 / 100
Specifications and access
| Specification | Value and source |
|---|---|
| Weights | ProprietarySource |
| Access | APISource |
| Context window | 400,000 tokensSource |
| Knowledge cutoff | August 31, 2025Source |
| Notes | 400K context, parameter count not disclosedSource |
| API model ID | gpt-5.4-nanoSource |
| Maximum output | 128,000 tokensSource |
| Input | Text, ImageSource |
| Output | TextSource |
| Reasoning mode | none, low, medium, high, xhighSource |
| API interfaces | Responses API, Chat Completions APISource |
| Tool calling | YesSource |
| Structured output | YesSource |
| Release | 2026-03-17Source |