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Data as of October 29, 2026 · How the score is built

EstablishedProprietaryReasoning

Released Mar 17, 2026400K context

GPT-5.4 mini

Decision readingGPT-5.4 mini scores 53 out of 100 and ranks #90 of 216. This profile shows 22 source-displayable benchmark rows; its strongest eligible category is Multimodal & Grounded at #29. API pricing is $0.75 input and $4.5 output per million tokens, with cached input at $0.075.

Released Mar 17, 2026 — see all recent releases

Decision snapshot

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

53/100

field median 50.5#90 of 216 ranked models

Public

#90of 216

Verified #45 of 77

Price

$0.75input / $4.50 output

input median $0.75cached $0.075 · blended $2.63

Speed

201tok/s

field median 92 tok/sFirst token 3.85 s

Context

400Ktokens

field median 256,000Maximum output length is tracked separately

Strongest published evidence

Multimodal & Grounded ranks #29. Particularly strong for screenshots, documents, charts, and grounded multimodal workflows.

Validate before choosing

22 published rows leave some tracked benchmark slots empty. Agentic is its lowest eligible category at #84.

Source-linked · 22 displayable benchmark rows

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #84 of 135Percentile 38thWeight 22%6 benchmarksVerified
36.4
CodingRank #80 of 156Percentile 49thWeight 20%5 benchmarksVerified
35.3
ReasoningRank Not rankedWeight 17%2 benchmarksVerified
43.7
MultimodalRank #29 of 58Percentile 51stWeight 12%2 benchmarksVerified
74.0
KnowledgeRank #77 of 179Percentile 57thWeight 12%5 benchmarksMixed sources
50.5
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingRank #30 of 157Percentile 81stWeight 5%Not listedUnlisted sources
89.9
MathRank Not rankedWeight 5%2 benchmarksVerified
55.9

22 of 782 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How much of this is verified

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.

  1. Agentic6/6 verified
  2. Coding5/5 verified
  3. Reasoning2/2 verified
  4. Multimodal2/2 verified
  5. Knowledge4/5 verified
  6. MultilingualNot measured
  7. Inst. FollowingNot measured
  8. Math2/2 verified
Verified sourceProvisionalNot measured

Capability shape

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 mini category percentile values

  • Agentic38th percentile
  • Coding49th percentile
  • ReasoningNot eligible
  • Multimodal51st percentile
  • Knowledge57th percentile
  • MultilingualNot eligible
  • Instruction following81st percentile
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#84/135
  2. Coding#80/156
  3. ReasoningNot ranked
  4. Multimodal#29/58
  5. Knowledge#77/179
  6. MultilingualNot ranked
  7. Inst. Following#30/157
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

Benchmark ledger

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.

Coding5 rows
Coding benchmark values, best verified comparison, weight, and source status
LiveCodeBench (Vals)LiveCodeBench, Vals AI runScore81.5%Versus best verified row

Best verified: Claude Fable 5.1 · 90.5%

Gap9 behindWeight8% ref. weight
FrontierCode 1.1 MainScore27.0%Versus best verified row

Best verified: Claude Opus 5.5 · 54.4%

Gap27.4 behindWeight4% ref. weight
Terminal-Bench 2.0Score60.0%Versus best verified row

Best verified: GPT-5.5 · 82.0%

Gap22 behindWeightScored in Agentic
Vibe Code BenchVibe Code Bench v1.1Score47.97%Versus best verified row

Best verified: Gemini 4 Argon · 91.90%

Gap43.9 behindWeightDisplay only
SWE-bench (Vals)SWE-bench, Vals AI runScore73.0%Versus best verified row

Best verified: Claude Opus 5 · 97.0%

Gap24 behindWeightDisplay only
Agentic6 rows
Agentic benchmark values, best verified comparison, weight, and source status
Terminal-Bench 2.0Score60%Versus best verified row

Best verified: GPT-5.5 · 82%

Gap22 behindWeight7% ref. weight
OSWorld-VerifiedScore72.1%Versus best verified row

Best verified: Qwen3.8 Max · 86.1%

Gap14 behindWeight7% ref. weight
MCP AtlasScore57.7%Versus best verified row

Best verified: Muse Spark Open · 89.2%

Gap31.5 behindWeight4% ref. weight
Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI runScore54.7%Versus best verified row

Best verified: GPT-6 Astra · 87.3%

Gap32.6 behindWeight4% ref. weight
ToolathlonScore42.9%Versus best verified row

Best verified: Muse Spark 1.1 · 75.6%

Gap32.7 behindWeight3% ref. weight
τ²-bench resultsτ²-Bench Tool-Agent-User EvaluationScore93.4%Versus best verified row

Best verified: GPT-5.4 · 98.9%

Gap5.5 behindWeightDisplay only
Reasoning2 rows
Reasoning benchmark values, best verified comparison, weight, and source status
ARC-AGI-2Abstraction and Reasoning Corpus for AGI v2Score18.9%Versus best verified row

Best verified: GPT-6 Astra · 95%

Gap76.1 behindWeightWeighted 25%
ARC-AGI-1ARC-AGI-1 Semi-Private EvaluationScore63.70%Versus best verified row

Best verified: Claude Fable 5 · 98.50%

Gap34.8 behindWeightDisplay only
Multimodal2 rows
Multimodal benchmark values, best verified comparison, weight, and source status
MMMU-ProMassive Multi-discipline Multimodal Understanding ProScore76.6%Versus best verified row

Best verified: GPT-6.1 Terra · 85.5%

Gap8.9 behindWeightWeighted 40%
MMMU-Pro w/ PythonMMMU-Pro with PythonScore78%Versus best verified row

Best verified: Kimi K3.1 Pro · 90%

Gap12 behindWeightDisplay only
Knowledge5 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLEHumanity's Last ExamScore41.5%Versus best verified row

Best verified: Kimi K3.1 Pro · 70%

Gap28.5 behindWeight44% ref. weight
HLE w/o toolsHumanity's Last Exam without toolsScore28.2%Versus best verified row

Best verified: Claude Opus 5.5 · 64.4%

Gap36.2 behindWeight7% ref. weight
MMLU-Pro (Vals)MMLU-Pro, Vals AI runScore84.6%Versus best verified row

Best verified: Claude Fable 5.1 · 92.4%

Gap7.8 behindWeight6% ref. weight
GPQAGraduate-Level Google-Proof Q&AScore88%Versus best verified row

Best verified: GPT-6 Astra · 96%

Gap8 behindWeight3% ref. weight
GPQA Diamond (Vals)GPQA Diamond, Vals AI runScore83.1%Versus best verified row

Best verified: Gemini 3.1 Pro · 95.5%

Gap12.4 behindWeight2% ref. weight
Math2 rows
Math benchmark values, best verified comparison, weight, and source status
FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3Score51.228%Versus best verified row

Best verified: GPT-6 Astra · 93.684%

Gap42.5 behindWeightWeighted 30%
FrontierMath v2 (Tier 4)FrontierMath v2 Tier 4Score9.756%Versus best verified row

Best verified: GPT-6.1 Sol · 100.000%

Gap90.2 behindWeightWeighted 10%

Bars run 0–100; the dark tick marks the best source-verified value

All 22 rows

What it costs to get this score

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.

Current modelExplore all models

GPT-5.4 mini · 53.0 score · $2.63 blended per million tokens

The chart opens on the current model. Scroll horizontally to inspect the full price axis.

405060708090100$0.10$0.50$1$5$10$25$50$100↘ frontierGPT-5.4 mini

Horizontal: blended price per million tokens, log scale · Vertical: public score

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Aug 7, 2025

    GPT-5 mini

    Score 47.9 · $0.25 / $2

  2. Mar 17, 2026 · you are here

    GPT-5.4 mini

    Score 53.0 · $0.75 / $4.5

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
text, imageOpenAI model catalog
Output modalities
textOpenAI model catalog
Parameters
Not disclosed by the provider
Availability
OpenAI Responses APIOpenAI model catalog
Cloud regions
Not tracked yet
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Published at $0.075 per million cached input tokensOpenAI pricing
Self-host
Weights are not published
Rate limits
Not tracked yet

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

GPT-5.4 mini ranks #90 of 216 on the public leaderboard with a score of 52.98/100. Its source-verified position is #45 of 77.

GPT-5.4 mini 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.

GPT-5.4 mini sits in the GPT-5.4 family with GPT-5.4, GPT-5.4 nano, GPT-5.4 Pro. Its explicit predecessor is GPT-5 mini. 22 of 782 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Multimodal & Grounded at #29, while its lowest eligible position is Agentic at #84. particularly strong for screenshots, documents, charts, and grounded multimodal workflows.

Last updated October 29, 2026. Runtime fields remain blank until a sourced snapshot exists.

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Where to run GPT-5.4 mini by API

OpenRouter is the one host we track that publishes a per-token price for it. Prices read from each host’s own pages on October 20, 2026.

Inference hosts for GPT-5.4 mini with input, output and cached-input prices per million tokens.
HostInput /1MOutput /1MCached /1MContext
OpenRouter$0.75$4.50$0.075400K
Compare inference hosts

Questions

How does GPT-5.4 mini perform overall in AI benchmarks?

GPT-5.4 mini ranks #90 out of 216 models on the public BenchAlign leaderboard, with a score of 52.98/100. Its evidence status is Supported, and this profile shows 22 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is GPT-5.4 mini good for knowledge and understanding?

GPT-5.4 mini ranks #77 out of 179 eligible models for knowledge and understanding, with a public category score of 50.5/100. 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.

Is GPT-5.4 mini good for coding and programming?

GPT-5.4 mini ranks #80 out of 156 eligible models for coding and programming, with a public category score of 35.3/100. 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.

Is GPT-5.4 mini good for mathematics?

GPT-5.4 mini 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.

Is GPT-5.4 mini good for reasoning and logic?

GPT-5.4 mini has source-displayable benchmark coverage for reasoning and logic, 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.

Is GPT-5.4 mini good for agentic tool use and computer tasks?

GPT-5.4 mini ranks #84 out of 135 eligible models for agentic tool use and computer tasks, with a public category score of 36.4/100. 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.

Is GPT-5.4 mini good for multimodal and grounded tasks?

GPT-5.4 mini ranks #29 out of 58 eligible models for multimodal and grounded tasks, with a public category score of 74/100. 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.

Which sibling models are related to GPT-5.4 mini?

GPT-5.4 mini belongs to the GPT-5.4 family. Related tracked variants include GPT-5.4, GPT-5.4 nano, 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.

Does GPT-5.4 mini have full benchmark coverage on BenchLM?

No. GPT-5.4 mini currently has 41 source-displayable rows. 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.

What is the context window size of GPT-5.4 mini?

GPT-5.4 mini 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.

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Compare GPT-5.4 mini with every tracked model1003 comparisons