GPT-5.4 nano
Not tested yet
Language modelActive
GPT-5.4 nano
OpenAI
- Released
- March 17, 2026
- Data date
- September 8, 2026
- Intelligence
- Overall score
- Speed
- 176.1 tokens/sOutput throughput
- Price
- Input · Output / 1M tokens
- Input
- Text, Image
- Output
- Text
No published category-wide ranking is available for this model.
Entries 1-12 of 128. Page 1 of 11.
Published benchmarks
Each chart compares models in the same documented test and highlights the current model.
Coding
3 measurementsCode Migration
Overall
Higher is better35 modelsGPT-5.4 nano: Rank 26 of 35Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-code-migration:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 35
- Methodology and context
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 1594.162. Cost per task in USD: 0.416225. Source ID: vals-ai. Evidence capture ID: vals-code-migration-2026-09-04-37e66450d0d6. Source payload hash: 37e66450d0d6f681e77c4fe9942f74c0aa743078002f50aef50932407223f88f. Parser version: vals-astro-v2. Imported at: 2026-09-04
IOI
Overall
Higher is better24 modelsGPT-5.4 nano: Rank 16 of 24Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-ioi:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 24
- Methodology and context
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Latency in seconds: 1170.492. Cost per task in USD: 0.042833. Source ID: vals-ai. Evidence capture ID: vals-ioi-2026-09-04-c6f99e8d7130. Source payload hash: c6f99e8d713092dbfdc9cbcfd6b376fbb7209970714528eab31f6b541d90f20c. Parser version: vals-astro-v2. Imported at: 2026-09-04
LiveCodeBench v6
Overall
Higher is better56 modelsGPT-5.4 nano: Rank 23 of 56Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-lcb:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 56
- Methodology and context
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 60.089. Cost per task in USD: 0.002468. Source ID: vals-ai. Evidence capture ID: vals-lcb-2026-09-04-95ca83387127. Source payload hash: 95ca83387127df287e9a6d928c411c98c9b65b4cefeee46eb4008ca1521f5ed4. Parser version: vals-astro-v2. Imported at: 2026-09-04
Finance
6 measurementsCorpFin v2
Exact Pages
Higher is better2 modelsGPT-5.4 nano: Rank 1 of 2Data date: August 11, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-corp-fin-v2:2:exact_pages
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 2
- 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: 2026-08-06. 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_v2-2026-08-11-d9e58d191cd9. Source payload hash: d9e58d191cd9f1690e3b59f0a37055813038531410f2d73e765676893c0f9526. Parser version: vals-astro-v2. Imported at: 2026-08-11
CorpFin v2
Max Fitting Context
Higher is better2 modelsGPT-5.4 nano: Rank 1 of 2Data date: August 11, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-corp-fin-v2:2:max_fitting_context
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 2
- 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: 2026-08-06. 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_v2-2026-08-11-d9e58d191cd9. Source payload hash: d9e58d191cd9f1690e3b59f0a37055813038531410f2d73e765676893c0f9526. Parser version: vals-astro-v2. Imported at: 2026-08-11
CorpFin v2
Overall
Higher is better50 modelsGPT-5.4 nano: Rank 27 of 50Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-corp-fin-v2:2:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 50
- Methodology and context
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-12. Latency in seconds: 9.397. Cost per task in USD: 0.01612. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-09-04-46dad6684551. Source payload hash: 46dad668455190ee4239b7c743d00d81c6fd3127e0d87123c518ec107c13b44d. Parser version: vals-astro-v2. Imported at: 2026-09-04
CorpFin v2
Shared Max Context
Higher is better2 modelsGPT-5.4 nano: Rank 2 of 2Data date: August 11, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-corp-fin-v2:2:shared_max_context
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 2
- 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: 2026-08-06. 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_v2-2026-08-11-d9e58d191cd9. Source payload hash: d9e58d191cd9f1690e3b59f0a37055813038531410f2d73e765676893c0f9526. Parser version: vals-astro-v2. Imported at: 2026-08-11
EMB
Overall
Higher is better32 modelsGPT-5.4 nano: Rank 25 of 32Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-emb:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 32
- Methodology and context
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 1767.043. Cost per task in USD: 0.57312. Source ID: vals-ai. Evidence capture ID: vals-emb-2026-09-04-5d630bb9b3a7. Source payload hash: 5d630bb9b3a7674ec91efa385ebf472ae6d8bb96c8db2fa2dd5af3e813e66155. Parser version: vals-astro-v2. Imported at: 2026-09-04
Finance Agent (v2)
Overall
Higher is better33 modelsGPT-5.4 nano: Rank 29 of 33Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-finance-agent-v2:2:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 33
- Methodology and context
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 334.538. Cost per task in USD: 0.15925. Source ID: vals-ai. Evidence capture ID: vals-fabv2-2026-09-04-88f92e979bb6. Source payload hash: 88f92e979bb632f19bdb1ae6ca2768ced7b2b2b915ea3aac1553be06fa197204. Parser version: vals-astro-v2. Imported at: 2026-09-04
GPQA Diamond
Overall
Higher is better54 modelsGPT-5.4 nano: Rank 40 of 54Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-gpqa:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 54
- Methodology and context
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 29.498. Cost per task in USD: 0.001565. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-09-04-fc438726f0d8. Source payload hash: fc438726f0d8523d320f02d75ae372a3fa38b28b36f70fe318d119f55153560d. Parser version: vals-astro-v2. Imported at: 2026-09-04
Legal
2 measurementsHarvey's Legal Agent Benchmark
Overall · Task fully resolved
Higher is better34 modelsGPT-5.4 nano: Rank 26 of 34Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-legal-agent-benchmark:1:overall
- Metric
- task resolution rate
- Scale
- 0-100
- Participants
- 34
- Methodology and context
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-03. Latency in seconds: 363.015. Cost per task in USD: 0.184287. Source ID: vals-ai. Evidence capture ID: vals-hlab-2026-09-04-211eab6c865f. Source payload hash: 211eab6c865f7c6808000150de043c5f65dd420c200156b06c68b58057fbd685. Parser version: vals-astro-v2. Imported at: 2026-09-04
LegalBench
Overall
Higher is better53 modelsGPT-5.4 nano: Rank 42 of 53Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-legal-bench:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 53
- Methodology and context
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 2.697. Cost per task in USD: 0.000114. Source ID: vals-ai. Evidence capture ID: vals-legal_bench-2026-09-04-ff81649923fb. Source payload hash: ff81649923fb684ff37d5f557fd320ba5ab433927831065ed781a94548f480ef. Parser version: vals-astro-v2. Imported at: 2026-09-04
Recorded measurement details
Every observation retains its source value and published test conditions.
Code Migration: Overall (Show measurement, test conditions, and source)
- Source value
- 14.467
- Score
- 14.467
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- coding
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-code-migration:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-04
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 1594.162. Cost per task in USD: 0.416225. Source ID: vals-ai. Evidence capture ID: vals-code-migration-2026-09-04-37e66450d0d6. Source payload hash: 37e66450d0d6f681e77c4fe9942f74c0aa743078002f50aef50932407223f88f. Parser version: vals-astro-v2. Imported at: 2026-09-04
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
- 2026-08-11
- 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: 2026-08-06. 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_v2-2026-08-11-d9e58d191cd9. Source payload hash: d9e58d191cd9f1690e3b59f0a37055813038531410f2d73e765676893c0f9526. Parser version: vals-astro-v2. Imported at: 2026-08-11
- 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
- 2026-08-11
- 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: 2026-08-06. 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_v2-2026-08-11-d9e58d191cd9. Source payload hash: d9e58d191cd9f1690e3b59f0a37055813038531410f2d73e765676893c0f9526. Parser version: vals-astro-v2. Imported at: 2026-08-11
- 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
- 2026-09-04
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-12. Latency in seconds: 9.397. Cost per task in USD: 0.01612. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-09-04-46dad6684551. Source payload hash: 46dad668455190ee4239b7c743d00d81c6fd3127e0d87123c518ec107c13b44d. Parser version: vals-astro-v2. Imported at: 2026-09-04
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
- 2026-08-11
- 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: 2026-08-06. 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_v2-2026-08-11-d9e58d191cd9. Source payload hash: d9e58d191cd9f1690e3b59f0a37055813038531410f2d73e765676893c0f9526. Parser version: vals-astro-v2. Imported at: 2026-08-11
- Comparison methodology
- Reasoning effort: high. Maximum output tokens: 128000
EMB: Overall (Show measurement, test conditions, and source)
- Source value
- 44.751
- Score
- 44.751
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- finance
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-emb:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-04
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 1767.043. Cost per task in USD: 0.57312. Source ID: vals-ai. Evidence capture ID: vals-emb-2026-09-04-5d630bb9b3a7. Source payload hash: 5d630bb9b3a7674ec91efa385ebf472ae6d8bb96c8db2fa2dd5af3e813e66155. Parser version: vals-astro-v2. Imported at: 2026-09-04
Finance Agent (v2): Overall (Show measurement, test conditions, and source)
- Source value
- 38.217
- Score
- 38.217
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 2
- Category
- finance
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-finance-agent-v2:2:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-04
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 334.538. Cost per task in USD: 0.15925. Source ID: vals-ai. Evidence capture ID: vals-fabv2-2026-09-04-88f92e979bb6. Source payload hash: 88f92e979bb632f19bdb1ae6ca2768ced7b2b2b915ea3aac1553be06fa197204. Parser version: vals-astro-v2. Imported at: 2026-09-04
GPQA Diamond: Overall (Show measurement, test conditions, and source)
- Source value
- 77.526
- Score
- 77.526
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- reasoning
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-gpqa:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-04
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 29.498. Cost per task in USD: 0.001565. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-09-04-fc438726f0d8. Source payload hash: fc438726f0d8523d320f02d75ae372a3fa38b28b36f70fe318d119f55153560d. Parser version: vals-astro-v2. Imported at: 2026-09-04
IOI: Overall (Show measurement, test conditions, and source)
- Source value
- 15.25
- Score
- 15.25
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- coding
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-ioi:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-04
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Latency in seconds: 1170.492. Cost per task in USD: 0.042833. Source ID: vals-ai. Evidence capture ID: vals-ioi-2026-09-04-c6f99e8d7130. Source payload hash: c6f99e8d713092dbfdc9cbcfd6b376fbb7209970714528eab31f6b541d90f20c. Parser version: vals-astro-v2. Imported at: 2026-09-04
LiveCodeBench v6: Overall (Show measurement, test conditions, and source)
- Source value
- 84.009
- Score
- 84.009
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- coding
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-lcb:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-04
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 60.089. Cost per task in USD: 0.002468. Source ID: vals-ai. Evidence capture ID: vals-lcb-2026-09-04-95ca83387127. Source payload hash: 95ca83387127df287e9a6d928c411c98c9b65b4cefeee46eb4008ca1521f5ed4. Parser version: vals-astro-v2. Imported at: 2026-09-04
Harvey's Legal Agent Benchmark: Overall · Task fully resolved (Show measurement, test conditions, and source)
- Source value
- 0
- Score
- 0
- Metric
- task resolution rate
- Unit
- %
- Benchmark version
- 1
- Category
- legal
- Task
- overall
- Task label
- Overall · Task fully resolved
- Direction
- Higher is better
- Comparison cohort
- vals-legal-agent-benchmark:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-04
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-03. Latency in seconds: 363.015. Cost per task in USD: 0.184287. Source ID: vals-ai. Evidence capture ID: vals-hlab-2026-09-04-211eab6c865f. Source payload hash: 211eab6c865f7c6808000150de043c5f65dd420c200156b06c68b58057fbd685. Parser version: vals-astro-v2. Imported at: 2026-09-04
LegalBench: Overall (Show measurement, test conditions, and source)
- Source value
- 77.92
- Score
- 77.92
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- legal
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-legal-bench:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-04
- Methodology
- Source model ID: openai/gpt-5.4-nano-2026-03-17. Source model name: GPT-5.4 nano. Model snapshot: gpt-5.4-nano-2026-03-17. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 2.697. Cost per task in USD: 0.000114. Source ID: vals-ai. Evidence capture ID: vals-legal_bench-2026-09-04-ff81649923fb. Source payload hash: ff81649923fb684ff37d5f557fd320ba5ab433927831065ed781a94548f480ef. Parser version: vals-astro-v2. Imported at: 2026-09-04
Our model tests
Community tests you can inspect
Compare how the models respond to the same prompt. Each test shows the first attempt, with no subsequent fixes to the generated code. These results do not contribute to an overall score.
Pelican on a bicycle
A community classic for free-form SVG drawing.
Prompt and test conditions
Generate an SVG of a pelican riding a bicycle
Token limit including reasoning: 8,192 tokens
Task origin (Simon Willison)Profile
Specifications and access
Published information about this model. Existing estimates are explicitly labeled.
Additional source observations
Dated documentation and model-card observations. Provider limits, native context and extended context can differ. Configuration notes retain the source wording.
- API model ID
- gpt-5.4-nanoSource
- Maximum output
- 128,000 tokensSource
- Knowledge cutoff
- 2025-08-31Source
- 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
Pricing
Published prices
Prices apply to the stated unit. Resolution, output length, and provider can change the cost.
Cost example
100 API requests
$0.0825
100 requests with 1,000 input and 500 output tokens each calculate to $0.0825. Input accounts for $0.02; output accounts for $0.0625.
- Input price
- $0.2 / 1M tokensBase tier for each request
- Output price
- $1.25 / 1M tokensBase tier for each request
The calculation uses documented token prices and no cache discount. It excludes extra tools, tax, reasoning tokens, and further hidden output tokens.
Open sourceHead-to-head comparisons
Compare this model
Each matchup compares this model with exactly one other model from the same category.
There are no published direct comparisons for this model yet.
Evidence
Sources and data date
Every statement links to its underlying documentation or leaderboard.
- Speed
OpenAI, xhigh effort. Output speed after the first streaming chunk, not total response time. Classified as deprecated by Artificial Analysis. Artificial Analysis maintains only the default 10K-input workload there. Retrieved September 8, 2026.
- Price
Base API prices without caching or batch discounts. Higher context tiers and other rates are listed under Costs.
- Input
Documented modalities. Retrieved September 8, 2026.
- Output
Documented modalities. Retrieved September 8, 2026.
Research date September 8, 2026. 4 source URLs checked. This documents the inspected sources, not an exhaustive inventory of every publication.
Open evidence questions and research notes (original wording)
Not found in the inspected sources
parameters-billions. OpenAI does not publish parameter counts.
Not found in the inspected sources
independent-benchmarks. The evaluated rows in this artifact are the exact OpenAI release-table entries; no independent evaluator row was merged.
- Model metadata (retrieved September 8, 2026)Source
- API pricingSource
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved September 4, 2026)Source
- Vals AI (retrieved September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved September 4, 2026)Source
- Vals AI (retrieved September 4, 2026)Source
- Vals AI (retrieved September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved September 4, 2026)Source
- OpenAI (retrieved September 8, 2026)Source
- Artificial Analysis (retrieved September 8, 2026)Source
- Speed measurement methodologySource