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Model details

OpenAI: GPT Luna Latest

OpenAI GPT Luna Latest is presented as a pointer entry that always redirects to the newest version within the GPT Luna family, following the same naming convention OpenRouter uses for sibling entries such as GPT Astra Latest, GPT Sol Latest, and GPT Terra Latest. This "Latest" alias pattern is meant to insulate applications from having to track individual version rollups, so code that references the alias continues to resolve to whatever model OpenAI considers current within the family at request time. Because the supplied catalog page groups GPT Luna under the OpenAI creator namespace and uses the standard "~openai/" key prefix, the entry is attributed to OpenAI as the originating developer rather than to any hosting or routing layer listed on the same page.

Practically, GPT Luna Latest is positioned alongside other recent OpenAI "Latest" aliases that each carry their own context, pricing, and capability profiles, which means the specific practical strengths of GPT Luna are not something the cataloged evidence confirms in isolation. What the public listing does establish is that the model is meant to be treated as a moving target that tracks the GPT Luna family's evolution, with downstream users expected to inherit whatever improvements, expanded context handling, or refined reasoning the family adopts over time. For teams evaluating it, the sensible fit is the same use case the GPT Luna family is designed around: staying on a continuously refreshed OpenAI model line without manual version pinning, while accepting that concrete benchmarks and capability details will track the underlying version rather than the alias itself.

Kilo Gateway~openai/gpt-luna-latestgpt-luna

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Provider
Kilo Gateway
Model key
~openai/gpt-luna-latest
Release date
Sep 11, 2026
Last updated
Sep 11, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.10
Output token cost
$0.50

Limits

Output tokens
128,000 tokens
Context window
1,050,000 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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