GPT-6 Luna
GPT-6 Luna is a chat model from OpenAI, tracked here with third-party throughput measurements of roughly 151 output tokens per second and about 1.46 seconds to first token.
| Provider | Input / 1M | Output / 1M | Cached / 1M |
|---|---|---|---|
| $0.020 | $0.100 | $0.0020 | |
| $0.025 | $0.125 | $0.0025 | |
| $0.050 | $0.250 | $0.0050 | |
| $0.080 | $0.400 | $0.0080 | |
| $0.100 | $0.500 | $0.010 | |
| $0.100 | $0.500 | $0.010 | |
| $0.100 | $0.500 | $0.010 | |
| $0.100 | $0.500 | - | |
| $0.100 | $0.500 | $0.010 | |
| $0.120 | $0.600 | $0.012 |
Prices updated daily. Last check: Nov 7, 2026
Compare API pricing for every OpenAI model →GPT-6 Luna pricing by provider
Input, output, and batch rates, plus alternatives, for one provider at a time.
Performance & Benchmarks
Source: Artificial Analysis →Benchmarks measured Nov 2026. Scores are independent evaluations, not vendor-reported.
Model Details
General
- Creator
- OpenAI
- Modalities
- Text
Capabilities
- Open Source
- No
Strengths & Limitations
Strengths
- Measured output throughput of approximately 150.7 tokens per second in third-party testing, which supports streaming chat interfaces
- Time to first token of roughly 1.46 seconds, giving a predictable initial latency budget for interactive applications
- Distributed as a chat-completion style model, so it slots into existing OpenAI-compatible client code without rearchitecting request handling
- Carries OpenAI's GPT naming, meaning tooling, SDKs, and prompt patterns built for other GPT chat models generally transfer
- Performance figures sourced from Artificial Analysis rather than vendor-published marketing numbers
- Listed across providers on this page, so cost per token can be compared directly against alternative chat models
Limitations
- We do not currently track a confirmed context window size for GPT-6 Luna, so long-document workloads need verification against OpenAI's documentation
- Supported input and output modalities are not recorded in our database — assume text chat unless OpenAI's docs state otherwise
- No standardized reasoning, coding, or knowledge benchmark scores are held in our catalog for this model, making direct quality comparison harder
- A time to first token near 1.5 seconds is noticeable in latency-sensitive voice or autocomplete use cases
- Measured throughput and latency vary by provider and load; the figures shown are averages, not service guarantees
Key Features
About GPT-6 Luna
Common Use Cases
GPT-6 Luna is positioned as a general chat model, which makes it a candidate for conversational assistants, drafting and rewriting text, summarization, question answering over supplied context, and back-office automation where responses are generated and streamed to a user. Its measured throughput of roughly 151 tokens per second means long-form responses render at a readable pace in a streaming UI, while the ~1.46 second time to first token is acceptable for chat but less suited to autocomplete, voice turn-taking, or other sub-second interaction loops. Because our database does not record a confirmed context window or multimodal support for this model, teams planning retrieval-heavy pipelines, very long document ingestion, or image input should confirm those capabilities in OpenAI's documentation before committing. For batch or high-volume classification work, compare its per-token cost in the pricing table against smaller models, since serving speed alone rarely determines total job cost.
Frequently Asked Questions
How much does GPT-6 Luna cost to use?
Pricing depends on which provider you route through and on the pricing type — input tokens, output tokens, and any cached or batch rates are billed separately, and providers change rates frequently. Check the pricing table on this page for the current per-provider figures rather than relying on a quoted number.
What is GPT-6 Luna best used for?
It is a chat model, so it fits conversational assistants, text drafting and editing, summarization, and question answering against context you supply in the prompt. Its measured ~151 tokens per second output speed suits streaming chat interfaces where the user reads the response as it arrives.
How fast is GPT-6 Luna?
Artificial Analysis measurements recorded in our database put output throughput at about 150.7 tokens per second with a time to first token around 1,460 milliseconds. Those are averages — actual numbers shift with provider, prompt length, and traffic levels.
What context window does GPT-6 Luna support?
We do not currently have a confirmed context window recorded for GPT-6 Luna in our database. Consult OpenAI's official model documentation for the authoritative limit before designing a long-context or retrieval-heavy pipeline around it.
Is GPT-6 Luna a good choice for latency-critical applications?
Its roughly 1.5 second time to first token is fine for typical chat, where a short pause before streaming begins is expected, but applications like voice turn-taking or inline code autocomplete generally target lower initial latency. Compare its time-to-first-token figure against other models listed on this site if that metric drives your decision.