Capability
66/100
field median 57.3
#28 of 216 ranked models
Model profile · OpenAI
Data as of July 31, 2026 · How the score is built
Knowledge ranks #46. Particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.
13 published rows leave some tracked benchmark slots empty. Coding is its lowest eligible category at #103.
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
66/100
field median 57.3
#28 of 216 ranked models
Price
$0.20input / $1.25 output
input median $1
cached $0.020 · blended $0.72
Speed
191tok/s
field median 107 tok/s
First token 3.64 s
Context
400Ktokens
field median 256,000
Maximum output length is tracked separately
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
GPT-5.4 nano category percentile values
The dashed outline is median of 6 nearest peers.
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Horizontal: blended price per million tokens, log scale · Vertical: public score
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #95 of 130Percentile 27thWeight 22%5 benchmarksVerified | 41.4 | #95 of 130 | 27th | 22% | 5 benchmarks | Verified |
| CodingRank #103 of 131Percentile 22ndWeight 20%1 benchmarkVerified | 42.6 | #103 of 131 | 22nd | 20% | 1 benchmark | Verified |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeRank #46 of 55Percentile 17thWeight 12%3 benchmarksMixed sources | 54.9 | #46 of 55 | 17th | 12% | 3 benchmarks | Mixed sources |
| MathRank Not rankedWeight 5%2 benchmarksVerified | 44.5 | Not ranked | Not available | 5% | 2 benchmarks | Verified |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalRank Not rankedWeight 12%2 benchmarksVerified | 16.4 | Not ranked | Not available | 12% | 2 benchmarks | Verified |
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Vibe Code BenchVibe Code Bench v1.1 | Score26.10% | Versus best verified row Best verified: Claude Opus 4.7 · 71.00% | Gap44.9 behind | WeightDisplay only | Benchmark exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.0 | Score46.3% | Versus best verified row Best verified: GPT-5.6 Sol · 91.9% | Gap45.6 behind | WeightWeighted 38% | Provider exact |
| OSWorld-Verified | Score39% | Versus best verified row Best verified: Claude Mythos 5 · 85% | Gap46 behind | WeightWeighted 34% | Provider exact |
| MCP Atlas | Score56.1% | Versus best verified row Best verified: Muse Spark 1.1 · 88.1% | Gap32 behind | WeightDisplay only | Provider exact |
| Toolathlon | Score35.5% | Versus best verified row Best verified: Muse Spark 1.1 · 75.6% | Gap40.1 behind | WeightDisplay only | Provider exact |
| τ²-bench resultsτ²-Bench Tool-Agent-User Evaluation | Score92.5% | Versus best verified row Best verified: GPT-5.4 · 98.9% | Gap6.4 behind | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| HLEHumanity's Last Exam | Score37.7% | Versus best verified row Best verified: Claude Opus 5 · 64.7% | Gap27 behind | WeightWeighted 45% | Provider exact |
| GPQAGraduate-Level Google-Proof Q&A | Score82.8% | Versus best verified row Best verified: Sakana Fugu-Ultra · 95.5% | Gap12.7 behind | WeightWeighted 7% | Reported |
| HLE w/o toolsHumanity's Last Exam without tools | Score24.3% | Versus best verified row Best verified: Claude Mythos 5 · 59% | Gap34.7 behind | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3 | Score25.860% | Versus best verified row Best verified: GPT-5.6 Sol · 89.000% | Gap63.1 behind | WeightWeighted 30% | Benchmark exact |
| FrontierMath v2 (Tier 4)FrontierMath v2 Tier 4 | Score6.250% | Versus best verified row Best verified: GPT-5.6 Sol · 83.000% | Gap76.8 behind | WeightWeighted 10% | Benchmark exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMMU-ProMassive Multi-discipline Multimodal Understanding Pro | Score66.1% | Versus best verified row Best verified: GPT-5.4 Pro · 94% | Gap27.9 behind | WeightWeighted 45% | Provider exact |
| MMMU-Pro w/ PythonMMMU-Pro with Python | Score69.5% | Versus best verified row Best verified: GPT-5.6 Sol · 84.6% | Gap15.1 behind | WeightDisplay only | Provider exact |
The sequence follows explicit supersedes links. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Aug 7, 2025
GPT-5 nanoNot publicly ranked · $0.05 / $0.4
Mar 17, 2026 · you are here
GPT-5.4 nanoScore 66.0 · $0.2 / $1.25
Nano
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
GPT-5.4 nano ranks #28 of 216 on the public leaderboard with a score of 65.99/100. Its source-verified position is #24 of 103.
GPT-5.4 nano is a proprietary model with a 400K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Official exact-value snapshot sourced from OpenAI's GPT-5.4 mini and nano launch materials.
GPT-5.4 nano sits in the GPT-5.4 family with GPT-5.4, GPT-5.4 mini, GPT-5.4 Pro. Its explicit predecessor is GPT-5 nano. 13 of 371 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Knowledge at #46, while its lowest eligible position is Coding at #103. particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.
GPT-5.4 nano ranks #28 out of 216 models on the public BenchAlign leaderboard, with a score of 65.99/100. Its evidence status is Supported, and this profile shows 13 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
GPT-5.4 nano ranks #46 out of 55 eligible models for knowledge and understanding, with a public category score of 54.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
GPT-5.4 nano ranks #103 out of 131 eligible models for coding and programming, with a public category score of 42.6/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
GPT-5.4 nano has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
GPT-5.4 nano ranks #95 out of 130 eligible models for agentic tool use and computer tasks, with a public category score of 41.4/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
GPT-5.4 nano has source-displayable benchmark coverage for multimodal and grounded tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
GPT-5.4 nano belongs to the GPT-5.4 family. Related tracked variants include GPT-5.4, GPT-5.4 mini, GPT-5.4 Pro. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
No. GPT-5.4 nano currently has 29 source-displayable rows across 371 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
GPT-5.4 nano has a documented context window of 400K. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.
Related resources
Last updated July 31, 2026. Runtime fields remain blank until a sourced snapshot exists.
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