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GPT-5.6 Luna (max)

★ featured
OpenAI · released 2026-07-09 · 10 offers

Output 130 tokens/sFirst token 92 sContext 1M tokens

Top 5 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.

#ProviderAdjusted $/task
1Azure
2Amazon Bedrock
3Azure AI Foundry
4AWS Bedrock
5T-Systems LLM Hub

Composite

5 of 7 inputs · 2 from the model family6 radar axes: DesignArena's two boards share one

79.3

includes −1.1 for its Benchmaxxing signal (from 80.4; why, switch off in Options)

dominance-adjusted from 82.2: a better-measured model that is at least as good on each of these inputs ranks above it

AA CodingCoding Agent v1.4AA IntelligenceAA AgenticEpoch ECISoftware ECIDesignArenaAA Coding: percentile 82Coding Agent v1.4: percentile 51AA Intelligence: percentile 93Epoch ECI: percentile 72Software ECI: percentile 61

AA Coding 71.4Coding Agent v1.4 57.2AA Intelligence 37.5AA Agentic —Epoch ECI 156.3Software ECI 156.0DesignArena —/—

Radar: percentile among all models measured on each input; a gap means not measured.

Benchmark sheet

47 of 140 registered benchmark versions · bars show the percentile among all models measured on each benchmark.

Composite attachments (used in the score, not counted as exact benchmarks):
  • Epoch ECI · attached
  • Software ECI · attached
Compare this model →

Agentic

  • APEX-Agents-AA8635.8%

    APEX-Agents-AA published 2026-09-10 ↗ · Published board — Tests professional-service tasks that require agents to produce locally graded deliverables.

  • AA-Briefcase781,339 Elo

    AA-Briefcase published 2026-09-10 ↗ · Published board — Tests multi-week professional knowledge-work projects with linked tasks and large source collections.

  • GDPval-AA v2861,489 Elo

    GDPval-AA v2 v2 ↗ · Published board — Tests professional knowledge-work deliverables across occupations using AA's Stirrup harness.

  • Harvey LAB-AA6487.9%

    Harvey LAB-AA published 2026-09-10 ↗ · Published board — Tests legal-work deliverables across practice areas on Harvey's private task set. Artificial Analysis' run, graded by one LLM judge against task rubrics — not the same run or scale as Vals AI's HLAB row.

  • ITBench-AA7540.3%

    ITBench-AA published 2026-09-10 ↗ · Published board — Tests root-cause diagnosis from offline Kubernetes incident snapshots.

  • Terminal-Bench v2.1 (AA)8380.9%

    Terminal-Bench v2.1 (AA) v2.1 ↗ · Published board — Tests terminal-based work on the 89-task verified refresh using Terminus 2.

  • Terminal-Bench v4.0 (AA)7111.6%

    Terminal-Bench v4.0 (AA) v4.0 ↗ · Published board — Tests terminal-based work on the 66-task release using mini-SWE-agent v2.4.6.

  • ApprenticeBench CUA (NeoCognition)187.0%

    ApprenticeBench CUA (NeoCognition) published 2026-09-14 ↗ · Codex — A computer-use agent operates the Odoo ERP through its screens across 100 sequential accounts-payable tasks with diminishing mentoring.

  • ApprenticeBench API (NeoCognition)013.0%

    ApprenticeBench API (NeoCognition) published 2026-09-14 ↗ · Codex — An agent completes the same 100 sequential accounts-payable tasks in the Odoo ERP with diminishing mentoring, using dedicated application API calls instead of the screen interface.

  • Vals Index v2 (Vals AI)7059.9%

    Vals Index v2 (Vals AI) v2 ↗ · Published board — GDP-weighted average of agentic model performance across finance, coding and legal tasks.

  • Finance Agent v2 (Vals Index v2)6055.0%

    Finance Agent v2 (Vals Index v2) v2 ↗ · Published board — Multi-step financial reasoning tasks.

  • Terminal-Bench 2.1 (Vals Index v2)8279.0%

    Terminal-Bench 2.1 (Vals Index v2) v2 ↗ · Published board — Command-line interface problem solving, as run by Vals AI.

  • HLAB — Harvey's Legal Agent Benchmark (Vals Index v2)111.3%

    HLAB — Harvey's Legal Agent Benchmark (Vals Index v2) v2 ↗ · Published board — Long-horizon legal work product creation. Vals AI's run of Harvey's Legal Agent Benchmark, reported as accuracy — not comparable with Artificial Analysis' Harvey LAB-AA row.

Coding

  • Artificial Analysis Coding Agent Index v1.46857.2%

    Artificial Analysis Coding Agent Index v1.4 v1.4 ↗ · Codex — The retained AA Coding Agent Index measures coding-agent systems using the earlier three-component implementation.

  • SciCode (AA subproblems) v1.0.17353.6%

    SciCode (AA subproblems) v1.0.1 ↗ · Published board — Tests scientific Python programming with scientist-annotated background information.

  • CursorBench 4.0 (Cursor) v4.0no percentile35.9%

    CursorBench 4.0 (Cursor) v4.0 ↗ · Published board — Agent evaluation on ambiguous, multi-file tasks drawn from real Cursor sessions.

  • Vibe Code Bench (Vals Index v2)6177.1%

    Vibe Code Bench (Vals Index v2) v2 ↗ · Published board — End-to-end app-building tasks.

  • Code Migration (Vals Index v2 subset)7244.8%

    Code Migration (Vals Index v2 subset) v2 ↗ · Published board — Porting projects to another language, including COBOL modernization.

  • FrontierCode 1.1 Main (Cognition) v1.1no percentile39.8%

    FrontierCode 1.1 Main (Cognition) v1.1 ↗ · codex — Whether a maintainer would merge the agent's pull request, on tasks crafted by open-source maintainers and graded with tests, rubrics and verifiers.

  • DeepSWE (Datacurve, via Epoch AI)6867.2%

    DeepSWE (Datacurve, via Epoch AI) published 2026-09-15 ↗ · mini-swe-agent — Pass rate of coding agents on original, long-horizon software engineering tasks, run by Datacurve with the mini-swe-agent harness.

  • VulcanBench Frontier v46784.1%

    VulcanBench Frontier v4 v4 ↗ · Codex — 23 behavioural-reconstruction tasks: the model must repair a replacement implementation of a legacy program until hidden tests confirm it reproduces the program’s real drift from its written spec; the combined score weights functional correctness 50%, lint/complexity 8.5%, security 8.5% and judged Code quality 33%.

  • AA Coding Index8271.4

    AA Coding Index published 2026-09-19 ↗ · Published board — Artificial Analysis publishes this board without a version number; we keep the date each result was retained.

Efficiency

Knowledge

Long-context

  • GDP.pdf (AA)8824.0%

    GDP.pdf (AA) published 2026-09-10 ↗ · Published board — Tests professional reasoning over long PDFs with AA document preparation and grading.

  • AA-LCR v1.19883.7%

    AA-LCR v1.1 v1.1 ↗ · Published board — Tests reasoning across multiple long documents with corrected answer keys and grading.

  • MLCR-AA6819.4%

    MLCR-AA published 2026-09-10 ↗ · Published board — Tests medical-record synthesis and reasoning across long, fragmented case documents.

Math

  • FrontierMath Tiers 1–3 v2 (Epoch AI)7682.1%

    FrontierMath Tiers 1–3 v2 (Epoch AI) v2 ↗ · Published board — Unpublished, expert-written mathematics problems from undergraduate to research level with automatically checkable answers, run by Epoch AI on its private v2 set.

  • FrontierMath Tier 4 v2 (Epoch AI)6361.0%

    FrontierMath Tier 4 v2 (Epoch AI) v2 ↗ · Published board — The hardest, research-level tier of Epoch AI's unpublished FrontierMath problems, run by Epoch AI on its private v2 set.

Reasoning

  • Chess Puzzles (Epoch AI)7640.0%

    Chess Puzzles (Epoch AI) published 2026-09-18 ↗ · Published board — Best-move selection on 100 novel chess positions generated programmatically by Epoch AI, each with a single Stockfish-verified best move; probes spatial reasoning and planning.

  • Mystery Game Puzzles (Epoch AI)3221.0%

    Mystery Game Puzzles (Epoch AI) published 2026-09-18 ↗ · Published board — Best-move selection on 100 mid-game positions of a well-known game whose identity Epoch deliberately keeps undisclosed, generated programmatically like Chess Puzzles.

  • AA Intelligence Index9337.5

    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.

Safety/Alignment

Science

Tool-use

  • AutomationBench-AA v1.0.67350.2%

    AutomationBench-AA v1.0.6 ↗ · Published board — Tests multi-app SaaS workflows through REST tools on a held-out AutomationBench split.

  • EnterpriseOps-Gym-AA5240.8%

    EnterpriseOps-Gym-AA published 2026-09-10 ↗ · Published board — Tests enterprise workflows through MCP tools against resettable application environments.

  • τ³-Banking (AA) v1.0.17031.1%

    τ³-Banking (AA) v1.0.1 ↗ · Published board — Tests banking support agents that retrieve policies and change account state through tools.

  • Excel Modeling Benchmark (Vals Index v2)7267.1%

    Excel Modeling Benchmark (Vals Index v2) v2 ↗ · Published board — Building and editing financial models in spreadsheets.

Vision

Unusual results

1 threshold-crossing signal flagged · 38 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 strong CritPt (AA) published 2026-09-10
    Why
    Observed: 0.20571 fraction
    Peer mean 0.03928 · peer sd 0.07596 · n 522 · families 369
    Directed z 2.191 · baseline z 0.613 · gap 1.579 · profile n 37
    0.20571 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗
    Evidence
    Axis: CritPt (AA) · published 2026-09-10 · Published board
    Exact value: 0.205714285714286 fraction
    Observed: 2026-09-10T21:47:16.627Z · publication date: not recorded
    Observation id: aa:426d24c8-49ae-482a-b4a8-20f1c53f21c1:critpt
Missing coverage · 96 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)

VariantAA CodingAA Intelligence
GPT-5.6 Luna (max)71.437.5
GPT-5.6 Luna (xhigh)68.634.8
GPT-5.6 Luna (high)63.332.4
GPT-5.6 Luna (medium)50.725.5
GPT-5.6 Luna (low)44.221.5
GPT-5.6 Luna (Non-reasoning)39.316.1

SUBSCRIPTION PLAN

GitHub Copilot

Current usage-based billing · model token cost is converted to AI Credits at 1 credit = $0.01.

Input $0.200 / 1M
Cached input $0.020 / 1M
Cache write $0.250 / 1M
Output $1.20 / 1M
Status GA
Token offers by platform · 8 offers (Adjusted $/task)

Click any underlined price to see how it is estimated and where each input comes from. How we calculate adjusted cost.

8 offers within the active global filters; “—” means the catalog is active but no public token price is available.

OpenRouter (4)

Azure
Azure
Amazon Bedrock
Azure

Azure AI Foundry (2)

Azure AI Foundry
Azure AI Foundry

AWS Bedrock (1)

AWS Bedrock

T-Systems LLM Hub (1)

T-Systems LLM Hub
GPT-5.6 Luna (max) — benchmarks & cost | Benchmark Heaven