OpenAI · GPT-5.6 Luna · July 2026

GPT-5.6 Luna — lightweight model built for low latency and high-frequency calls

  • Million-token context
  • Extra-long single replies
  • Fastest posture in the family
  • Built for high-throughput loads
GPT-5.6 Luna

What is GPT-5.6 Luna?

GPT-5.6 Luna is OpenAI’s speed-oriented GPT-5.6 model, released in July 2026. It targets chat drafts, classification, summarization, and short-turn automation: within the family it prioritizes responsiveness and throughput, while still clearly stronger than earlier lightweight generations. Everyday balanced work belongs on Terra; the heaviest long-horizon jobs belong on Sol. On iMini Agent, pick GPT-5.6 Luna to use it.

Vendor
OpenAI
Released
July 2026
Context
1M tokens
Max output
128K tokens
Deep reasoning
Tunable · lightweight posture
Best as
High-turnover and short-turn primary

Where it shines

Speed, throughput, and the shared family surface—boundaries to know before putting Luna in a pipeline.

Faster and leaner in the family

OpenAI positions Luna as the fastest, most affordable GPT-5.6 option—suited to moving large volumes of short jobs off heavier models.

Still keeps million-token context

Context and output ceilings match the family, so short-turn jobs can still carry longer materials without jumping to Terra or Sol first.

Fits the front of a pipeline

Classification, summarization, drafts, and routing can run on Luna first; escalate to Terra or Sol when deeper checking is needed.

Shares the generation’s tool surface

Hooks into GPT-5.6 reasoning and tool-use capabilities so Agent flows can switch tiers step by step.

Official evaluations

Results OpenAI published with GPT-5.6. The shared x-axis is output-token volume. Luna is the family’s fastest tier, yet several scores still sit above the prior flagship.

Agents' Last Exam: long-horizon professional workflow score
Covers long-horizon workflows across 55 industries. Luna scores 50.3—nearly matching Terra (50.4)—and clearly above Claude Fable 5 (40.5). A lightweight model posting long-job scores above another vendor’s flagship.
Artificial Analysis Intelligence Index v4.1 composite intelligence index
Third-party composite intelligence index. Luna’s curve sits below Sol and Terra overall, but at matched output volume it tracks GPT-5.5—everyday intelligence doesn’t drop a tier just to go faster.
Artificial Analysis Coding Agent Index v1.1 coding-agent index
Third-party coding-agent index. Luna at 74.6 sits within a modest gap of Claude Fable 5 (77.2). For light, high-frequency coding and test-fill work, Luna’s cost–performance curve is the best in the family.
Terminal-Bench 2.1: command-line software engineering tasks
Command-line software engineering. Luna at 84.7% beats GPT-5.5’s launch figure of 83.4%. Prior-flagship terminal work is now reachable on the fastest tier.
BrowseComp: multi-step web retrieval and verification
Multi-step web retrieval. Luna’s curve rises steadily with output volume—summaries, verification, and batch retrieval are where Luna shines for volume.
OSWorld 2.0: graphical desktop computer use
GUI computer-use eval. Luna tracks GPT-5.5 while using less output. Note: critical complex desktop jobs still prefer Terra or above.
AutomationBench: end-to-end business workflow pass rate
End-to-end business workflow eval. Luna beats the GPT-5.4 generation; simple, well-specified automation can batch on Luna—escalate longer flows to Terra.
GDPval-AA v2: real knowledge-work Elo
Real knowledge-work Elo. Luna and Terra curves stay tight—drafts, classification, and everyday writing get the highest per-token yield in the family on Luna.

Three common workflows

GPT-5.6 Luna fits short turns, high concurrency, and relatively controllable failure cost.

Drafts & rewrites

For first drafts and tone rewrites of email, explainers, and product copy. Ship a draft quickly, then proof critical spots on a heavier model.

Classification, extraction & summarization

For labels, field extraction, and meeting-note summaries. Focus on stable formats and high throughput.

Short-turn agent automation

For tool calls with few steps and a clear goal. Hard-code success criteria; send root-cause work and repo-scale changes to Sol.

How to choose vs GPT-5.6 Terra and GPT-5.6 Sol

Three tiers in one generation. The differences are depth, throughput, and the failure cost you can accept.

DimensionGPT-5.6 LunaGPT-5.6 TerraGPT-5.6 Sol
Context1M tokens1M tokens1M tokens
ReasoningLighter and fasterBalanced depthMax depth · ultra available
Coding / agentsShort-turn drafts & light automationDay-to-day coding & mid-weight agentsHeaviest long-horizon coding
Long tool runsHigh turnover, shorter threadsMore balanced completion and throughputFlagship depth + ultra
Speed postureResponsiveness and throughput firstEveryday primary favors balanceCompletion quality first
Prefer whenDrafts, classification, and short-turn automationEveryday coding and high-volume businessHighest failure-cost, heaviest jobs

Using GPT-5.6 Luna on iMini

Free quota, model naming, key specs, and how it differs from Terra and Sol.

Use GPT-5.6 Luna free on iMini Agent

Million-token context, faster responses, built for high-turnover work.

Open GPT-5.6 Luna

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