GPT-5 nano (medium)
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 | Platform | Raw input $/1M | Raw output $/1M | Adjusted $/task |
|---|---|---|---|---|---|
| 1 | Azure | OpenRouter | $0.050 | $0.400 | |
| 2 | Azure AI Foundry | Azure AI Foundry | $0.050 | $0.400 |
Composite
3 of 7 inputs · 2 from the model family6 radar axes: DesignArena's two boards share one26.3
AA Coding —Coding Agent v1.4 —AA Intelligence 12.5AA Agentic —Epoch ECI 139.4Software ECI 140.7DesignArena —/—
Radar: percentile among all models measured on each input; a gap means not measured.
Benchmark sheet
15 of 140 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)5617.4%
Terminal-Bench Hard (AA) pinned revision 74221fb ↗ · Published board — Tests a pinned 44-task hard subset of terminal-based work using Terminus 2.
τ²-Bench Airline (OpenRouter run)2347.6%
τ²-Bench Airline (OpenRouter run) published 2026-09-15 ↗ · Published board — Multi-turn service agents making tool calls under strict policy constraints. (OpenRouter's own reproducible run, as published on openrouter.ai/benchmarks.)
Efficiency
GPQA Diamond (OpenRouter run) — measured cost per task60$0.013
GPQA Diamond (OpenRouter run) — measured cost per task published 2026-09-15 ↗ · Published board — Mean USD OpenRouter actually spent per task while running GPQA Diamond for this configuration.
τ²-Bench Airline (OpenRouter run) — measured cost per task54$0.043
τ²-Bench Airline (OpenRouter run) — measured cost per task published 2026-09-15 ↗ · Published board — Mean USD OpenRouter actually spent per task while running τ²-Bench Airline for this configuration.
Instruction-following
IFBench (AA single-turn)7765.9%
IFBench (AA single-turn) published 2026-09-10 ↗ · Published board — Tests precise single-turn instructions with deterministic rule checks.
LisanBench word chains, v0.2.0 (Lisan al Gaib)631,238
LisanBench word chains, v0.2.0 (Lisan al Gaib) v0.2.0 ↗ · Published board — A model builds the longest chain of English words it can, each differing from the last by one letter, with no repeats and only dictionary words, from 50 starting words; any broken rule ends the chain.
Knowledge
Humanity's Last Exam (AA text-only)508.7%
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 Index59-25.8
AA-Omniscience Index published 2026-09-10 ↗ · Published board — Tests factual reliability while rewarding correct answers and penalizing hallucinations.
Long-context
AA-LCR v1.14243.7%
AA-LCR v1.1 v1.1 ↗ · Published board — Tests reasoning across multiple long documents with corrected answer keys and grading.
Math
AIME 2025 (AA) v20257378.3%
AIME 2025 (AA) v2025 ↗ · Published board — Advanced mathematical problem solving on AIME I and II 2025.
Reasoning
AA Intelligence Index5412.5
AA Intelligence Index published 2026-09-19 ↗ · Published board — Artificial Analysis publishes this board without a version number; we keep the date each result was retained.
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)4467.0%
GPQA Diamond (AA) published 2026-09-10 ↗ · Published board — Tests graduate-level biology, physics and chemistry knowledge on the Diamond subset.
GPQA Diamond (OpenRouter run)2970.9%
GPQA Diamond (OpenRouter run) published 2026-09-15 ↗ · Published board — Graduate-level science questions that resist retrieval and reward careful reasoning. (OpenRouter's own reproducible run, as published on openrouter.ai/benchmarks.)
Tool-use
τ²-Bench Telecom (AA)3730.4%
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)2558.2%
MMMU Pro (AA) published 2026-09-10 ↗ · Published board — Tests multimodal understanding using challenging ten-option questions.
Missing coverage · 129 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 2026-09-19 · Data: Artificial Analysis · Data: Epoch AI (CC BY)
| Variant | AA Coding | AA Intelligence |
|---|---|---|
| GPT-5 nano (high) | — | 13.0 |
| GPT-5 nano (medium) | — | 12.5 |
| GPT-5 nano (minimal) | — | 7.1 |
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; “—” means the catalog is active but no public token price is available.
OpenRouter (2)
| 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)
| 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 |