AI Model Release Tracker

GPT-6 Luna

Released

GPT-6 Luna is an AI model released by OpenAI on Tuesday, Sep 22 2026, the same day as GPT-6 Sol. It has a 1.05M token context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider.. Benchmark results (shown below) cover BullshitBench v2, DeepSWE 1.1, Next.js Evals, Supabase Evals, Terminal-Bench 4.0, ARC-AGI-2, and 1 more.

API pricing

Up to 272K input tokens
InputWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it.
$0.10
Cached inputA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again.
$0.01
Cache writeA one-off charge for storing text so later requests can reuse it at the cheaper cached rate.
$0.125
OutputWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one.
$0.50
Over 272K input tokens
InputWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it.
$0.20
Cached inputA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again.
$0.02
Cache writeA one-off charge for storing text so later requests can reuse it at the cheaper cached rate.
$0.25
OutputWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one.
$0.75
  • Reasoning or thinking is supported.
  • OpenAI also publishes a Fast mode for this model at exactly twice the standard rate in every column — $0.20 per million input tokens and $1.00 per million output at short context.
USD per 1M tokensEvery price here is for one million tokens. A token is roughly three-quarters of a word, so a million tokens is about 750,000 words of text.Verified October 19, 2026Read from developers.openai.com. Click the check to open the source.

Available from

OpenAI—flex$0.05$0.251M
OpenAI——$0.10$0.501M
Amazon Bedrockglobal—$0.10$0.501M
Azure——$0.10$0.501M
Amazon Bedrockus-east-1—$0.11$0.551M
Azureeu—$0.11$0.551M
Azureus—$0.11$0.551M
OpenAI—fast$0.20$1.001M
USD per 1M tokensEvery price here is for one million tokens. A token is roughly three-quarters of a word, so a million tokens is about 750,000 words of text.Checked November 7, 2026Third-party rates from openrouter.ai, not the lab’s own list price.

Benchmarks

Coding

DeepSWE 1.1Agentic coding — Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. (Version 1.1 of the test.) Higher is better.
66.6%
#19 of 37
Next.js EvalsNext.js coding — Vercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better.
86%
#11 of 35
Supabase EvalsSupabase coding — Supabase's own open benchmark: a coding agent is dropped into a real Supabase project and asked to do real work — set up a schema, fix a broken security policy, debug an Edge Function — and every run is checked against a live Supabase stack. This is the headline number, where the agent has Supabase's own skills loaded, as most people building on Supabase would. The score is the share of scenarios it got right. Higher is better.
75.4%with skills
63.8%no skills
with skills
#9 of 11
no skills
#8 of 11

Terminal & CLI

Terminal-Bench 4.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Version 4.0 recalibrated how much time, CPU and memory each task gets, removed eight tasks and fixed nineteen, so fewer runs fail for reasons that have nothing to do with the model. Scores are not comparable with earlier versions. Higher is better.via Terminal-Bench
16.36%
#28 of 32

Reasoning & science

ARC-AGI-2Abstract reasoning — Puzzle-style tests of abstract reasoning and pattern-finding — the kind of thing people find easy but AIs often struggle with. Higher is better.via BenchLM
59.3%
#30 of 41

Robustness

BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better.
59%
#27 of 98

Community preference

threejsevalCommunity preference (Three.js) — Every model gets the same prompt — "the Eiffel Tower", "a glass fishbowl", "a robot arm picking toys into a box" — and builds a 3D scene in Three.js. Real people then see two scenes side by side, names hidden, and vote for the one they prefer. The votes become a chess-style Elo rating on threejseval.com, averaged across all the prompts. It measures whether the scene looks and moves right to a human eye, not whether the code passes a test. Higher is better.
1365
#22 of 29

Source: Terminal-Bench, retrieved 12 October 2026 · Source: BenchLM, retrieved 28 September 2026. Other sources are identified on the linked benchmark pages.

Compare GPT-6 Luna with

GPT-6 Luna

Suggested comparisons

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About

GPT-6 Luna was introduced in September 2026 as the smaller, efficiency-focused model in OpenAI's GPT-6 family, alongside Sol. OpenAI positioned it for frequent, focused tasks and offered it through the API and selected ChatGPT experiences. At launch, Free and Go users could access Luna in the desktop app, while access through other plans and interfaces followed the announced product rules.

The API documented text and image inputs, text output and a 1,050,000-token context window, with adjustable reasoning effort. Its smaller-tier role did not imply a short context limit or downloadable weights. The release emphasized lower operating cost for repeated work; performance and latency still depended on the chosen reasoning setting and surrounding application.

Frequently asked questions

GPT-6 Luna was released by OpenAI on Tuesday, Sep 22 2026.

All OpenAI releases

49 tracked

2022

1 release
GPT-3.5
Nov 30 2022