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ModelDeprecatedClosed / proprietaryIdentity probable

gpt-5-nano

OpenAIfamily · GPT 5developers.openai.com/api/docs/models/gpt-5-nano

Fastest, most cost-efficient version of GPT-5

Open in Graph
data quality72

Updated 5 h ago · first seen 11 Sept 2026

model_01M293V77R6FFYAT0QV1XNWCX4

Overview

Identity

Canonical model
Yesidentity confidence: mediumOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
Official checkpoints
None recorded — closed weightsofficial_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
Artifacts
None recordedSeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
Provider deployments
2
API aliases
gpt-5-nanogpt-5-nano-mediumgpt-5-nano-minimalopenai/gpt-5-nanoIdentifiers under which providers and evaluators refer to this model.
Folded evaluation variants
2Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.

Openness

Closed / proprietary— weights not available; 7 dimensions unknown.

Weights are not available; the model is reachable only through an API or a product.

  • Weights

    No

  • Inference code

    —

  • Training code

    —

  • Training data

    —

  • Dataset

    —

  • Commercial use

    —

  • Redistribution

    —

  • Derivatives

    —

dimensions marked null are unknown, not false

Key facts

Release date

Source:OpenRouter public model & pricing listingT2observed 17 h agomedium

Status

Source:OpenAI Platform docsT1observed 17 h agohigh

Knowledge cutoff

Source:OpenRouter public model & pricing listingT2observed 17 h agomedium

Deprecation date

Source:OpenAI Platform docsT1observed 17 h agohigh

Retirement date

Source:OpenAI Platform docsT1observed 17 h agohigh

Official page
developers.openai.com/api/docs/models/gpt-5-nano

Source:OpenAI Platform docsT1observed 17 h agohigh

API model id

Source:OpenAI Platform docsT1observed 17 h agohigh

Openrouter id

Source:OpenRouter public model & pricing listingT2observed 17 h agomedium

Architecture

Tokenizer

Source:OpenRouter public model & pricing listingT2observed 17 h agomedium

Capabilities

Modalities

Modalities
documentimagetext
Input
documentimagetext
Output
text

Capabilities

  • Tool calling

    Yes

    OpenRouter public model & pricing listing · T2

  • Structured output

    Yes

    OpenRouter public model & pricing listing · T2

  • Reasoning

    Yes

    OpenRouter public model & pricing listing · T2

  • Vision

    Yes

    OpenRouter public model & pricing listing · T2

  • Audio

    Unavailable

  • Fine-tuning available

    Unavailable

Context window

Source:OpenRouter public model & pricing listingT2observed 17 h agomedium

Max output

Source:OpenRouter public model & pricing listingT2observed 17 h agomedium

Knowledge cutoff

Source:OpenRouter public model & pricing listingT2observed 17 h agomedium

Tokenizer

Source:OpenRouter public model & pricing listingT2observed 17 h agomedium

Benchmarks43

Compare with another model →

Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric

Benchmark results grouped by comparability group
Benchmark · groupBest scoreTrustConfigurationResultsvs leaderEvaluatedSource
Terminal-Benchagentic · accuracy · variant=hard · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisvarianthardreasoning_effortmediumconditions differ across rows → partially comparable6−48.5 ptvs gpt-5.6-solobs. 12 Sept 2026artificialanalysis.aiT2
τ²-benchagentic · pass^1 · variant=Telecom · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantTelecomreasoning_efforthighconditions differ across rows → partially comparable3non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
τ²-benchagentic · pass^1 · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysis3−62.6 ptvs Z.ai GLM 5.2obs. 11 Sept 2026artificialanalysis.aiT2
SWE-bench Verifiedcoding · resolved · board=Verified · system=mini-SWE-agentOfficial boardboardVerifiedsystemmini-SWE-agentreasoning_effortmediumconditions differ across rows → partially comparable1−42.0 ptvs Claude Opus 4.57 Aug 2025swebench.comT2
Artificial Analysis Intelligence Indexcomposite · indexIndependentreasoning_efforthighversion4.3conditions differ across rows → partially comparable6−40.4vs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
IFBenchinstruction-following · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoning_efforthighconditions differ across rows → partially comparable6−15.8 ptvs Grok 4.3obs. 12 Sept 2026artificialanalysis.aiT2
Humanity's Last Examknowledge · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoning_efforthighconditions differ across rows → partially comparable6−49.6 ptvs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
MMMU-Promultimodal · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoning_efforthighconditions differ across rows → partially comparable6−25.9 ptvs gpt-6-astraobs. 12 Sept 2026artificialanalysis.aiT2
GPQA Diamondreasoning · accuracy · variant=Diamond · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantDiamondreasoning_efforthighconditions differ across rows → partially comparable3non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
GPQA Diamondreasoning · accuracy · variant=GPQA Diamond · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantGPQA Diamond3−28.7 ptvs gpt-6-astraobs. 11 Sept 2026artificialanalysis.aiT2

Current rows only, grouped by benchmark → canonical metric → comparability group (task configuration). Effort variants folded into this model appear as rows of the same group. 43 current rows in total. “vs leader” compares with the current leader of the benchmark's primary group only; other groups are not directly comparable. Comparability rules →

Providers & Pricing5

All offers in the price terminal →
Provider deployments, cheapest output first
ProviderContextInput / 1MCached inOutput / 1MBatch in / outNative unitsStatusObservedSource
OpenAI APIcheapest outputopenai/gpt-5-nano:batch400Kout 128K$0.0025——active7 h agosince 11 Sept 2026openrouter.aiT2
OpenRouteropenai/gpt-5-nano:batch400Kout 128K$0.0025——active1 h agosince 12 Sept 2026openrouter.aiT2
OpenAI APIgpt-5-nano—$0.005$0.025 / $0.20flex_input_per_mtok=0.025flex_output_per_mtok=0.2active9 h agosince 11 Sept 2026developers.openai.comT1
OpenAI APIopenai/gpt-5-nano400Kout 128K$0.005——active7 h agosince 11 Sept 2026openrouter.aiT2
OpenRouteropenai/gpt-5-nano400Kout 128K$0.005——active1 h agosince 12 Sept 2026openrouter.aiT2

USD per 1M tokens as published by each provider; native units (per-request fees, flex/priority tiers) are kept verbatim. Rows are append-only — every price change is kept in the history below. Cost of a workload →

Price history

Step lines per provider; amber markers are recorded changes. Click a marker or a row for the evidence behind that price.

Output price · USD / 1M tokens 2 providers

Output price history of gpt-5-nano$0$0.10$0.20$0.30$0.40$0.50Sept 26Sept 26Sept 26Sept 26Sept 26OpenAI API: first observed → $0.40 · 11 Sept 2026OpenAI API: $0.40 → $0.20 · 11 Sept 2026OpenRouter: first observed → $0.40 · 12 Sept 2026OpenRouter: $0.40 → $0.20 · 12 Sept 2026
  • OpenAI API
  • OpenRouter
  • OpenRouter$0.40 → $0.2012 Sept 2026
  • OpenRouterfirst observed $0.4012 Sept 2026
  • OpenAI API$0.40 → $0.2011 Sept 2026
  • OpenAI APIfirst observed $0.4011 Sept 2026

Input price · USD / 1M tokens 2 providers

Input price history of gpt-5-nano$0$0.02$0.04$0.06Sept 26Sept 26Sept 26Sept 26Sept 26OpenAI API: first observed → $0.05 · 11 Sept 2026OpenAI API: $0.05 → $0.025 · 11 Sept 2026OpenRouter: first observed → $0.05 · 12 Sept 2026OpenRouter: $0.05 → $0.025 · 12 Sept 2026
  • OpenAI API
  • OpenRouter
  • OpenRouter$0.05 → $0.02512 Sept 2026
  • OpenRouterfirst observed $0.0512 Sept 2026
  • OpenAI API$0.05 → $0.02511 Sept 2026
  • OpenAI APIfirst observed $0.0511 Sept 2026

Versions & Artifacts0

Version history

Context windowfirst observation only

11 Sept 2026current

Knowledge cutofffirst observation only

11 Sept 2026current

Max outputfirst observation only

11 Sept 2026current

Opennessfirst observation only

11 Sept 2026current

Statusfirst observation only

11 Sept 2026current

Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.

Artifacts 0

No artifact (checkpoint, quantisation, conversion or packaging) points to this model yet.

Timeline26

Full timeline →

Change history

Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.
1 claims · 1 propertiesShow all properties

Aa context windowaa_context_window1

Claim history for Aa context window
ValueValid from → toStatusSourceConfidenceExtractor
400,000 tokens → currentcurrentArtificial AnalysisT2mediumdeterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

Provenance

Attributed facts

30

Source tiers

T1T29 / 21

Freshest observation

5 h ago

Conflicts

None

Source documents 6

Source documents
SourceDocumentTypeTierLast observedSnapshots
OpenAI Platform docsdevelopers.openai.com/api/docs/deprecations.md model_docsT1· Official1 h ago2
OpenAI Platform docsdevelopers.openai.com/api/docs/models.md model_docsT1· Official1 h ago1
OpenAI Platform docsdevelopers.openai.com/api/docs/pricing.md pricingT1· Official1 h ago2
OpenRouter public model & pricing listingopenrouter.ai/api/v1/models catalogueT2· Quality secondary1 h ago12
SWE-bench leaderboardsswebench.com/ leaderboardT2· Quality secondary6 h ago1
Artificial Analysisartificialanalysis.ai/leaderboards/models leaderboardT2· Quality secondary7 h ago2

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.

Data quality (72/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →