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OpenAI GPT-6 Luna Long (>272K Context) Chat Completions
x402
OpenAI GPT-6 Luna Long (>272K Context) Chat Completions is a paid API for AI agents from openai.mm.family, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-02).
Provides GPT-6 Luna chat completions with over 272K input token context window, billed per call in USDC via x402 protocol with tiered service levels.
Price / call$0.001
Success—
StatusUnknown
How this service works
gpt-6-luna-long: OpenAI GPT 6 Luna (>272K input tokens) chat completions, paid per call in USDC. Per 1M tokens in/out: Flex (default) 0.1/0.375, Standard 0.2/0.75, Fast 0.4/1.5; pick with service_tier. Plus $0.0005 (Base) or $0.0005 (Solana) per call; the quote charges input plus 10% of max_tokens. Levels: none, low, medium, high, xhigh (model gpt-6-luna-long:<level>). Empty answers are free. Rates: https://openai.mm.family/x402/pricing
Output
Returns a standard OpenAI-compatible chat completion JSON object including the assistant's reply, token usage breakdown (prompt, completion, total), finish reason, service tier used, and a unique completion ID. Empty responses incur no charge.
Example use cases
Long document Q&A with large context
“I have a 300-page research report I need analyzed — use GPT-6 Luna Long on flex tier with up to 2048 output tokens to answer: what are the top three findings and their supporting evidence?”
Complex agentic reasoning task
“Run this multi-step reasoning problem through GPT-6 Luna Long at xhigh reasoning level with standard service tier, allowing up to 8192 tokens in the response: given these 50 customer transcripts, identify recurring complaint patterns and propose solutions.”
Cost-efficient large-context generation
“I need GPT-6 Luna Long on flex tier to draft a detailed product specification from this 100,000-token requirements dump — keep the response under 3000 tokens to minimize cost.”
Technical details
Endpoint
POSThttps://openai.mm.family/x402/v1/models/gpt-6-luna-long/chat/completions?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need more than 272K tokens of input context with GPT-6 Luna specifically, or when cost optimization matters (flex tier is cheapest). Prefer over gpt-6-astra when your prompt exceeds the standard context limit. Use when you need USDC micropayment billing via x402 rather than traditional API key auth. Choose higher service tiers (standard, fast) when latency is critical.
Side effects
- Insufficient USDC balance — payment fails before completion is returned
- max_tokens quota exceeded causing truncated output
- Model overloaded at selected service_tier — try flex or auto tier
- Input exceeds 272K token context window — request rejected
- Invalid model variant string returns 400 error
- Streaming errors if network drops mid-response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| model | string | |
| tools | array | |
| stream | boolean | |
| messages | array | |
| max_tokens | integer | |
| service_tier | string | |
| response_format | object | |
| reasoning_effort | string |
Output
Schema · Response
{
"type": "json",
"example": {
"id": "chatcmpl-x",
"model": "gpt-6-luna-long",
"usage": {
"total_tokens": 9,
"prompt_tokens": 8,
"completion_tokens": 1
},
"object": "chat.completion",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello",
"refusal": null
},
"finish_reason": "stop"
}
],
"service_tier": "flex"
}
}Tags
x402
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