OpenAIOpenAI·💬 Text Generation·↑ Newer: GPT-5.6 Luna·New

GPT-6 Luna

ReasoningVisionFunction CallingWeb Searchanonymized
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Quick reference
GPT-6 Luna — TLDR
  • 📏 1.05M-token context: 922K input, 128K output
  • ⚡ OpenAI's most efficient GPT-6 tier for high-volume work
  • 👁️ Accepts text and image input, returns text
  • 🔧 Function calling, web search, Responses API tools
  • 🧠 Selectable reasoning effort from none up to max
  • 🆕 Successor to GPT-5.6 Luna, launched alongside GPT-6 Sol
  • 💬 Aimed at chat, classification, lightweight agentic workflows
  • 🎯 Served via Responses and Chat Completions APIs
💰 Pricing
$0.125 / $0.625
per 1M · input / output
📏 Context
1.1M tokens
📅 On Venice since
Sep 22, 2026
1 day ago
Provider

OpenAI is an American artificial intelligence research organization headquartered in San Francisco, structured as both a for-profit public benefit corporation and a nonprofit foundation. The lab developed the GPT family of large language models, the DALL-E…

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38 models on Venice
23 text · 4 image · 4 video · 4 inpaint · 2 embedding · 1 asr
Since Jan 15, 2025

About this model

GPT-6 Luna is the smallest, most cost-efficient member of OpenAI's GPT-6 lineup, released in September 2026 alongside GPT-6 Sol and sitting below the flagship GPT-6 Astra. OpenAI's own model guidance positions it for cost-sensitive, high-volume workloads, while Sol balances intelligence and cost and Astra handles the most complex reasoning and coding. It accepts text and images, emits text, and exposes a 1.05 million-token context window with up to 128K output tokens.

Compared with its direct predecessor, GPT-5.6 Luna, the continuity is notable: both share the same 1.05M-token window and the same selectable reasoning-effort ladder running from none through low, medium, high and max, plus vision input, function calling and hosted tools such as web search. The GPT-6 release refreshes this efficiency tier within the newer generation, so the same integration surface — Responses and Chat Completions — carries over for existing 5.6 Luna deployments.

Practically, Luna suits classification, extraction, routing, retrieval over very long documents, and focused agent steps, with reasoning effort dialled up when a task needs more deliberation and dialled down for latency-sensitive, high-throughput traffic. Teams needing deeper multi-step reasoning or heavier coding work are pointed by OpenAI's documentation toward Sol or Astra instead, keeping Luna as the volume workhorse of the family.

This About section is AI-generated from public sources (Claude Opus 5), with no human editing. It may contain inaccuracies — verify critical details against the sources listed above.

Data sources: Venice API · HuggingFace · Wikipedia — enrichment updated 2h ago