GPT-5 nano (Minimal)
Context 400K tokens
Top 2 cheapest providers (Adjusted $/task)
The same list price can give a different adjusted $/task (caching, token efficiency) — click a price for its inputs.
Within the active global provider, residency and confidentiality filters.
| # | Provider | Price channel | Raw input $/1M | Raw output $/1M | Adjusted $/task |
|---|---|---|---|---|---|
| 1 | Azurevia OpenRouter — Price via OpenRouter: OpenRouter's price for Azure's endpoint (https://openrouter.ai/openai/gpt-5-nano/providers), collected 2026-11-03. | via OpenRouter — Price via OpenRouter: OpenRouter's price for Azure's endpoint (https://openrouter.ai/openai/gpt-5-nano/providers), collected 2026-11-03. | $0.050 | $0.400 | |
| 2 | Azure AI Foundrydirect — Direct price: Azure AI Foundry's own price list (https://prices.azure.com/api/retail/prices), collected 2026-11-03. | direct — Direct price: Azure AI Foundry's own price list (https://prices.azure.com/api/retail/prices), collected 2026-11-03. | $0.050 | $0.400 |
Composite
3 of 7 inputs · 2 from the model family6 radar axes: DesignArena's two boards share one13.2
AA Coding v4.x —Coding Agent v1.4 —AA Intelligence (est.) 3.0AA Agentic —Epoch ECI 139.3Software ECI 140.6DesignArena —/—
Radar: percentile among all models measured on each input; a gap means not measured.
Benchmark sheet
10 of 319 registered benchmark versions · bars show the percentile among all models measured on each benchmark.
- Epoch ECI · attached
- Software ECI · attached
Agentic
Terminal-Bench Hard (AA)376.8%
Terminal-Bench Hard (AA) pinned revision 74221fb → · Published board — Tests a pinned 44-task hard subset of terminal-based work using Terminus 2.
Instruction-following
IFBench (AA single-turn)2032.5%
IFBench (AA single-turn) published 2026-09-10 → · Published board — Tests precise single-turn instructions with deterministic rule checks.
Knowledge
Humanity's Last Exam (AA text-only)134.0%
Humanity's Last Exam (AA text-only) published 2026-09-10 → · Published board — Tests expert-level knowledge on AA's text-only Humanity's Last Exam subset.
AA-Omniscience Index12-64.1
AA-Omniscience Index published 2026-09-10 → · Published board — Tests factual reliability while rewarding correct answers and penalizing hallucinations.
Long-context
AA-LCR v1.12320.0%
AA-LCR v1.1 v1.1 → · Published board — Tests reasoning across multiple long documents with corrected answer keys and grading.
Math
AIME 2025 (AA)2927.3%
AIME 2025 (AA) v2025 → · Published board — Advanced mathematical problem solving on AIME I and II 2025.
Science
CritPt (AA)240.0%
CritPt (AA) published 2026-09-10 → · Published board — Tests research-level physics reasoning with Python, symbolic and numerical answers.
GPQA Diamond (AA)1842.8%
GPQA Diamond (AA) published 2026-09-10 → · Published board — Tests graduate-level biology, physics and chemistry knowledge on the Diamond subset.
Tool-use
τ²-Bench Telecom (AA)3025.7%
τ²-Bench Telecom (AA) published 2026-09-10 → · Published board — Tests dual-control telecom agents that coordinate tool use with a simulated user.
Vision
MMMU Pro (AA)331.8%
MMMU Pro (AA) published 2026-09-10 → · Published board — Tests multimodal understanding using challenging ten-option questions.
Unusual results
1 threshold-crossing signal flagged · 10 eligible benchmark families
How flags are calculated
Heuristic screen, not statistical significance: benchmark families are correlated and source uncertainty is unknown. Peer evidence needs ≥ 20 independently measured matched configurations from ≥ 10 distinct model families. A flag needs a directed population z-score of magnitude ≥ 1.5 and a gap of ≥ 1.5 from the leave-one-benchmark-family-out mean z in the same direction, over ≥ 5 other benchmark families.
- unusually weak MMMU Pro (AA) published 2026-09-10
Why
Observed: 0.31792 fractionPeer mean 0.66323 · peer sd 0.1457 · n 276 · families 163Directed z -2.37 · baseline z -0.856 · gap -1.514 · profile n 90.31792 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗Evidence
Axis: MMMU Pro (AA) · published 2026-09-10 · Published boardExact value:0.317919075144509fractionObserved: 2026-09-10T21:47:16.627Z · publication date: not recordedObservation id:aa:05e45a36-b5c6-47a1-8adb-9ddc19add5b3:mmmuPro
Missing coverage · 309 benchmark versions
No result does not mean a zero, or that the model was never tested. Collection failures and disputed versions retain their distinct status.
Variants / reasoning settings
Artificial Analysis snapshot 2026-11-03 · Intelligence Index v5.0 (est. = estimated from v4, not measured) · Coding Index v4.x frozen 2026-10-27 · Data: Artificial Analysis · Data: Epoch AI (CC BY)
| Variant | AA Coding | AA Intelligence |
|---|---|---|
| GPT-5 nano (High) | — | 5.9est. |
| GPT-5 nano (Medium) | — | 5.4est. |
| GPT-5 nano (Minimal) | — | 3.0est. |
Token offers by platform · 4 offers (Adjusted $/task)
Click any underlined price to see how it is estimated and where each input comes from. How we calculate adjusted cost.
4 offers within the active global filters, 1 more outside them; “price n/a” means the provider serves the model but publishes no direct token price we could collect — no other channel's price is shown in its place.
OpenRouter (2)
Prices via OpenRouter — what OpenRouter charges for each provider's endpoint, not the provider's own direct price. Source: openrouter.ai/openai/gpt-5-nano/providers, collected 2026-11-03.
| Azure | globalazure | $0.050 raw in $/1M | $0.400 raw out $/1M | |
| Azure | euazure/swedencentralEU | $0.055 raw in $/1M | $0.440 raw out $/1M |
Azure AI Foundry (2)
Direct prices from Azure AI Foundry's own price list. Source: prices.azure.com/api/retail/prices, collected 2026-11-03.
| Azure AI Foundry | global | $0.050 raw in $/1M | $0.400 raw out $/1M | |
| Azure AI Foundry | euEU | $0.055 raw in $/1M | $0.440 raw out $/1M |