OpenAI · Fast, low-cost processing at scale
GPT-5.6 Luna
The most economical variant in the GPT-5.6 family for classification, extraction and other repetitive tasks where cost and speed outweigh maximum quality.
- Costs
- Low · standard rates from July 30, 2026: $0.20 per million input tokens and $1.20 per million output tokens
- Speed
- Fast; the paid Fast mode costs twice as much
- Availability
- OpenAI API and the Codex tool
- Input length
- Varies by product and mode
- Inputs
- Text and, depending on the service used, image inputs
Data checked . Release date unverified.
Indicative capability profile
Where the model is strong
The five levels are our clear summary of the results below. They are not a ranking that applies to every task.
Ideal use
When to choose it
- Classifying and labeling large volumes of text
- An initial low-cost pass before a stronger model
- Simpler automation with precisely controllable output
Usage boundaries
When to choose another model
- The hardest analyses and strategic decisions
- Complex programming without subsequent review
Traceable supporting sources
Data and measurement sources
Distinguish between the manufacturer's documentation and the results of a specific test. Measurements also depend on the settings and the task set used.
Variant identification
For efficient, high-volume processingThe company recommends Luna where low cost and high volume matter.
Open original source ↗Standard price after the price reduction
$0.20 input · $0.02 cached input · $1.20 outputAmounts are per million tokens in a short context; the price fell by 80%.
Open original source ↗Trends over time
Related events from AI Radar
OpenAI cuts prices for GPT-5.6 Luna and Terra models, says optimization of its own infrastructure by Sol made this possible
Anyone using OpenAI API for their own projects or tools with a low-cost model (Luna) will pay significantly less for the same work than before, as illustrated by Simon Willison, who switched from Gemini to Luna because of the price.
Companies running products on cheaper GPT-5.6 models can reduce inference costs by as much as tens of percent or consider switching from competing providers (Google, Anthropic), intensifying price pressure across the AI industry.
OpenAI halved prices for the GPT-6 Sol and Luna models; independent analysis does not confirm a performance improvement
New: Anthropic released Claude Opus 5.5 on the same day (2026-09-23), roughly an hour after OpenAI; Claude Opus 5.5 is 20% cheaper than the previous Opus 5.0 ($4/$20 vs $5/$25); Opus 5.5 improved communication style and token efficiency; The model releases launch a 'price war' between the two largest AI companies; GPT-6 Luna and Sol are part of a broader strategy of price competition, not an isolated release
Developers working with the API from OpenAI can reduce inference costs by up to half while maintaining the same usage pattern (Sol for more complex tasks, Luna for high-volume simple tasks), but independent tests suggest that a lower price may not mean higher or even the same output quality in all cases.
Businesses gain a cheaper option for reasoning models for high-volume or repetitive tasks (summaries, data extraction, code), but according to an independent analysis, actual output quality has not improved compared with the previous generation and has instead declined on some knowledge work tasks, so deployment decisions should not rely solely on the manufacturer's claims about price/performance.
OpenAI opens the Pro plan to new users, but halves API credits and moves toward payment for actual usage
New: API credits per dollar halved; Pro plan at $200/month reopened to new users; 5-hour window for the weekly allotment removed; Strategic shift from subsidized subscription models to pay-per-use pricing; Microsoft is making similar changes with Copilot
Users considering the OpenAI Pro plan at $200/month now also benefit from the removal of the 5-hour limit, but those paying through the API receive fewer credits for the same dollar than before — the new lower prices of the GPT-6 Sol and Luna models only partially offset this.
Companies using the OpenAI API should recalculate their AI operating costs, because the number of credits per dollar is changing and the price of the new GPT-6 Sol and Luna models has also fallen by 50 % compared with the 5.6 series — the net impact on the budget depends on the specific usage volume and types of models used.
GitHub Copilot reported a 51-minute outage affecting OpenAI models due to an upstream provider error
GitHub Copilot users who encountered errors with GPT-5.6 Luna, GPT-5.6 Terra, GPT-5.6 Sol, GPT-5.3-Codex or GPT-6 Astra during that window could work around the problem by selecting another model or the 'Auto' option.
The outage showed that the reliability of GitHub Copilot depends on the upstream provider of OpenAI models – the 51-minute degradation affected development teams using the affected models until the provider implemented a fix.
Next step
Compare the model using your actual task.
A benchmark narrows the selection. A short trial on your data determines the choice.