GPT-6 Luna

gpt-6-luna. The model card says to use that string in API requests, and the only snapshot listed is the same id. OpenAI describes it as the most efficient model for focused, high-volume tasks.

Chat Completions (v1/chat/completions) and Responses (v1/responses) are supported. Batch is supported. Realtime, Assistants, fine-tuning, embeddings, image generation, and the legacy Completions route are not supported.

Standard text rates on the model card: $0.10 input, $0.01 cached input, $0.125 cache writes, and $0.50 output, each per million tokens.

The long-prompt cliff is 272K input tokens, not a separate short-context product. Above that, OpenAI prices the full request at 2× input and cache rates and 1.5× output. A request that crosses the line does not keep the cheap rate on the first 272K.

Batch and Flex are 50% of Standard. Fast mode is 2× the applicable rates. Regional processing adds a 10% premium where available. EU data residency is listed for Standard, Fast, Flex, and Batch. This page does not quote a relay price.

1,050,000 context window. Maximum input tokens: 922,000. Maximum output tokens: 128,000. Knowledge cutoff: 18 May 2026. Reasoning tokens are supported.

Input modalities are text and image. Output is text. Supported features on the card: streaming, structured outputs, function calling, file search, image input, web search, and prompt caching.

Default rate-limit table on the same card, tier Build / Launch / Grow: RPM 5,000 / 10,000 / 30,000. TPM 2,000,000 / 10,000,000 / 180,000,000. Batch queue limit 20,000,000 / 1,000,000,000 / 15,000,000,000.

reasoning.effort supports none, low, medium (the default), high, xhigh, and max.

Built-in tools and function calling belong on the Responses API. Chat Completions supports function calling only when reasoning_effort is none. Responses tools listed on the card include web search, file search, image generation, code interpreter, hosted shell, apply_patch, skills, computer use, MCP, and tool search.

The API model card documents gpt-6-luna only. It does not say which snapshot the ChatGPT “GPT-6” label routes to, and it does not list plan eligibility.

A user report from the last two days: r/ChatGPT — OpenAI’s “GPT-6” branding in normal chat is highly manipulative marketing (9 October 2026, score 0, 15 comments). The post claims standard chat labeled GPT-6 is Sol or Luna, not Astra. Comments split between “Astra is not a chat model” and “the name still oversells it.” Treat that as a labeling argument, not as an API routing fact.

OpenAI’s API card prices tokens. It does not publish ChatGPT Plus quota math for Codex.

A user report from the last two days: r/codex — How do you guys feel about... (10 October 2026, score 1, 3 comments). The question is whether web ChatGPT at high, plus Codex Luna at high for research, planning, implementation, tests, review, and bugfixes, stays inside a Plus allowance for plugins, small programs, and userscripts. One comment says Luna can run continuously without hitting the 5-hour window and that its context is lower. Another says the plan has to be written into the repo or compaction eats it. Those are subscription reports, not API list-price measurements.

The model card lists one effort scale for the API: none through max, default medium. It does not say a Codex “high” selector maps onto API “low,” and it does not say the API gets more reasoning tokens than a subscription.

A user report from the last two days: r/codex — What to choose in todays world? (10 October 2026, score 0, 10 comments). The post claims API and subscription differ, with the example “luna high in codex = luna low in api.” A comment in the same thread says they pair GPT-6.1 Sol with GPT-6 Luna xHigh sub-agents and that the combination is slow. Treat both as user reports.

The API snapshot list is one id: gpt-6-luna. The card does not document a Luna Ultra model id.

A user report from the last two days: r/codex — 5.6luna ultra？ (10 October 2026, score 0, 2 comments). The poster says an Ultra option they remember on Luna is gone, and that ChatGPT told them Luna has no Ultra option. The comment says they never saw Ultra on Luna, while Sol and Astra had it early. That is a product-selector report, not a second API id.

The model card says Chat Completions is supported and that max output is 128,000 tokens. It does not name max_tokens or max_completion_tokens on this page.

A user report from the last two days: r/LeanBitLab_ — Chatgpt API Tokens (10 October 2026, score 2, 1 comment). The poster is on a keyboard client stuck on ChatGPT 4.1 because of a max_tokens limit, and asks whether GPT-6 Luna is usable when the client demands max_completion_tokens. The only comment says native support for that parameter is coming in a keyboard update. That is a client report, not an OpenAI error code.

OpenAI’s Luna card does not publish a coding-benchmark comparison against GPT-6.1 Sol. This page does not add one.

User reports from the last two days, not vendor scores: r/codex — Luna calling out 6.1 Sol for trying to cheat (9 October 2026, score 134, 32 comments). Comments say Luna is useful for review and security passes, and also that after Luna failed to fix something, Sol finished it. Separately, r/ClaudeCode — Claude Haiku 5.5: Anthropic is Cutting Prices (10 October 2026, score 0, 10 comments) claims Haiku 5.5 matches GPT-6 Luna on token price and is not necessarily cheaper per task. Price-per-token is the OpenAI card above. Cost per successful task is not on that card.