AI Model Profile

GPT-5.6 Luna

GPT-5.6 Luna is the cost-optimised tier of the GPT-5.6 family, retaining the full 1,050,000-token context window and reasoning-token support.

Family
GPT-5
Release date
Unknown
Status
Current
Context window
1,050,000 tokens
Output limit
128,000 tokens
API
yes
Open weights
no
Local/self-hosted
no
Pricing
$1.00 per million input tokens, $0.10 cached input, $6.00 per million output tokens. Batch API: $0.50 input, $0.05 cached, $3.00 output.
Evidence state
Recheck due

Benchmark Caveat

Benchmarks and provider capability notes are directional, not universal rankings. Results can shift with prompts, tool use, latency targets, pricing tier, safety filters, context length, and the workload mix a real team runs.

See the linked official model, docs, model-card, or pricing source for provider-published capability notes.

Best for

Cost-sensitive workloads that still need a very large context window and reasoning support.

Skip if

Skip if the workload needs the highest reasoning tier available in the family.

Strengths

OpenAI lists Luna with the same 1,050,000-token context window and 128,000 max output tokens as Sol and Terra, at the lowest price in the family, with a high reasoning tier, reasoning-token support, text and image input, and supported function calling.

Weaknesses

Reasoning tier is high rather than highest. Output is text only.

Agent suitability

Useful for agent workflows when the provider supports tool use, long context, structured outputs, or workflow-specific APIs.

Kingy AI take

Use this as a source-backed shortlist candidate, not a universal ranking. Re-check official provider docs and run a task-specific trial before production adoption.

Verification & Sources

Evidence state
Recheck due
Source links
2
Freshness
Needs recheck: checked July 25, 2026
Last updated
July 25, 2026
What this evidence state means
Definition
The claim was previously checked, but its review window expired or a material change may have invalidated it.
Required provenance
The prior evidence and check date are retained, together with the expiry or change signal that triggered recheck.
Owner
Kingy freshness queue owner and assigned editorial reviewer
Freshness rule
This is already outside its freshness rule. It must not be presented as current until reviewed against current evidence.
Disputes and corrections
Use “Suggest a correction” on the record. Kingy editorial reviews the cited evidence, records material corrections, and changes or removes the state when it is not supported.

Key source checks

Suggest a correction

Form submissions, correction notes, score details, URLs, and analytics events may be stored for editorial review, spam prevention, product improvement, and follow-up. Do not submit secrets, unreleased financials, private customer data, or regulated personal data through these forms.

Coding notes

Use official docs and live evals before selecting this model for production coding workflows.

Reasoning notes

Provider capability notes are useful but should be validated on representative prompts and tools.

Creative notes

Use a small creative test set before standardizing outputs for brand, media, or customer-facing work.

Research notes

Track release notes and model lifecycle notices because availability and aliases can change.

API pricing notes

Check the official pricing page before budget decisions; Kingy does not freeze token, credit, or subscription prices in model cards.

License notes

Commercial/API terms apply unless the linked official source states otherwise.

Hardware requirements

Cloud/API model; local hardware requirements are not published as a self-hosted path.