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GPT-6 Luna

by OpenAI

GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classi

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Models

GPT-6 Luna

Added 24 Sept 2026

#openai

Overview

GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic...

Best for

Best for
Cost-conscious everyday automation

How to use / API access

Call via OpenRouter with model id `openai/gpt-6-luna`.

  • openrouter · openai/gpt-6-luna Docs

OpenRouter id: openai/gpt-6-luna

Benchmarks

  • Intelligence Index (artificial-analysis): 38.1 index

Notes

GPT-6 Luna is listed in the EDNA Models directory from the OpenRouter catalogue.

Pros

  • Summarising short operational notes
  • file, image, text input; text output on the listed OpenRouter route

Cons

  • Assuming lower token prices guarantee lower total task cost
  • Using output without checking source fidelity
  • Catalogue base token rates have additional pricing overrides. Context length, time window, caching, reasoning, tools or media can change total cost; the simple calculator is not a full quote.
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USAGE / OPENROUTER

How much GPT-6 Luna is used

Tokens processed through OpenRouter each day. It shows what developers actually run, not every company's private traffic.

Tokens, last 7 days
6.3T ▼10.9%
Requests, last 7 days
406M
Tool calls, last 7 days
87.9M
Intelligence score
38.1
People's vote
1392
Average cost per request
8.6¢
Price per million tokens
$0.1 in · $0.5 out
01T2T22 Sept: 72.9B tokens, 2.7M requests23 Sept: 412B tokens, 24.3M requests24 Sept: 543B tokens, 31.4M requests25 Sept: 628B tokens, 26.1M requests26 Sept: 626B tokens, 24M requests27 Sept: 609B tokens, 23.5M requests28 Sept: 828B tokens, 34.2M requests29 Sept: 808B tokens, 34.9M requests30 Sept: 1.1T tokens, 44.5M requests1 Oct: 1.2T tokens, 48.3M requests2 Oct: 891B tokens, 42.2M requests3 Oct: 687B tokens, 34.4M requests4 Oct: 771B tokens, 32.8M requests5 Oct: 846B tokens, 41.7M requests6 Oct: 1T tokens, 52.9M requests7 Oct: 1.1T tokens, 51.9M requests8 Oct: 1.3T tokens, 54.8M requests9 Oct: 1.3T tokens, 57.8M requests10 Oct: 871B tokens, 45.3M requests11 Oct: 733B tokens, 43.5M requests12 Oct: 862B tokens, 53.9M requests13 Oct: 1T tokens, 58.3M requests14 Oct: 1.1T tokens, 61.1M requests15 Oct: 974B tokens, 59.6M requests16 Oct: 1T tokens, 66.1M requests17 Oct: 706B tokens, 57.7M requests18 Oct: 689B tokens, 48.9M requests22 Sept6 Oct18 OctSee where it ranks on the leaderboard →

MODEL FIELD GUIDE / SOURCE EVIDENCE

What you can do with GPT-6 Luna.

Specifications reviewed; no EDNA task evaluation has been run. Sources checked 2026-10-20. Hosting routes and app features can differ.

DeveloperOpenAI
Exact model identifieropenai/gpt-6-luna
Inputfile, image, text
Outputtext
Tool calling
Listed support
Structured output
Listed support
Reasoning controls
Listed support
Availability
available
Price basis
token
Licence verification
Check the developer licence; the model name is insufficient

Catalogue base token rates have additional pricing overrides. Context length, time window, caching, reasoning, tools or media can change total cost; the simple calculator is not a full quote.

Consider it for

  • Summarising short operational notes
  • Lightweight agents with narrowly scoped read-only tools

Watch for

  • Assuming lower token prices guarantee lower total task cost
  • Using output without checking source fidelity

PRACTICAL EXERCISE / NOT RUN BY ENTERPRISE DNA

Try the model on a small, checkable task.

Summarise: Order 41 arrived Monday; two units damaged; replacement requested Tuesday; no refund approved. Return status, next action and unresolved facts in three bullets.

Check the result: The summary retains the damaged count, replacement request and absence of a refund approval.

Compare another approach

anthropic claude sonnet 5 5 ↗openai gpt 6 1 sol ↗
Inspect the sources and their scope
provider source ↗

Developer documentation for model family or task. OpenRouter route-specific properties remain catalogue claims; EDNA has not executed a task evaluation.

Checked 2026-10-19
catalogue source ↗

openai/gpt-6-luna: listed route capabilities, availability and prices; provider endpoints can differ.

Checked 2026-10-20
How to evaluate a model for your work →

FROM SPECIFICATIONS TO YOUR WORK

Is this the right model for your job?

Start with a realistic sample. These workflows match the model’s listed capabilities, not a verified result on your task.

Extract document dataWorkflow & starter prompt ↗Run a reliable agentWorkflow & starter prompt ↗

Check the source

Price date: 2026-10-20. Prices are USD API token rates. Your app subscription, uploads, browsing and tools are separate.

Model source & availability ↗

Understand the evidence

Listed capabilities and third-party benchmark scores do not establish Enterprise DNA task-test results. Validate accuracy and total cost on your own sample.

Intelligence Index: 38.1 (2026-10-18) ↗
Compare this model with alternatives →