# GPT-6 Luna — API pricing & integration guide | Y-API

> GPT-6 Luna is the fast, cost-efficient member of the GPT-6 series, positioned below GPT-6 Sol. It accepts file, image and text input over a 1,050,000-token window and is aimed at high-volume, latency-sensitive work.

This is the markdown representation of https://y-api.bestvirtualgoods.com/models/openai/gpt-6-luna. Generated by `scripts/generate-seo-assets.mjs` from the same copy the page renders — do not edit by hand.

Model ID: `openai/gpt-6-luna`

Sources reviewed: 2026-10-11. Y-API catalog snapshot: 2026-10-11.

## Choosing this model

Selection advice by Y-API. The checks below are suggested evaluations, not published test results.

### Where to start

Try it for chat, classification and lightweight agent steps where the request volume is high and each individual call is simple enough that a larger model would be wasted on it.

### What to watch for

The low input price applies up to a token threshold; above it the listed rate roughly doubles, so very large requests do not scale linearly with the headline number. There is no publisher card to inspect for this closed-weight model.

## Model specifications

These are OpenRouter model-level specifications, not a Y-API compatibility test. A particular route may accept fewer input formats, parameters or tokens. Verify the features you need with a small request; a successful text response does not validate vision or tool calling.

| Field | Value |
| --- | --- |
| Context window | 1,050,000 tokens |
| Input | File, Image, Text |
| Output | Text |
| Listed on OpenRouter | 2026-09-22 |
| Parameters listed by OpenRouter | `include_reasoning`, `max_completion_tokens`, `max_tokens`, `reasoning`, `reasoning_effort`, `response_format`, `seed`, `structured_outputs`, `tool_choice`, `tools`, `verbosity` |

## API pricing & cost estimate

| Price basis | Input / 1M tokens | Output / 1M tokens |
| --- | --- | --- |
| Account credit | $0.10 | $0.50 |
| Cash equivalent | $0.01 | $0.05 |

$1 paid adds $10 of credit. Cash equivalent = credit consumed ÷ 10; this is not the model publisher’s list price.

Input tokens / request: 1000. Output tokens / request: 500. Number of requests: 1000.

Estimated credit consumed: $0.35. Estimated cash equivalent: $0.035.

Illustrative token budget, not measured usage or a quote. Includes input and output; excludes separate media charges, cache discounts and retries. Include billed reasoning tokens in your output budget where applicable. Actual billing follows usage returned by the service.

### Same token budget, different models

| Model | Estimated credit consumed | Estimated cash equivalent |
| --- | --- | --- |
| [GPT-6 Luna](https://y-api.bestvirtualgoods.com/models/openai/gpt-6-luna) | $0.35 | $0.035 |
| [GPT-5.6 Luna](https://y-api.bestvirtualgoods.com/models/openai/gpt-5.6-luna) | $0.95 | $0.095 |
| [Claude Haiku 5.5](https://y-api.bestvirtualgoods.com/models/anthropic/claude-haiku-5.5) | $0.45 | $0.045 |

[View LLM API pricing & billing](https://y-api.bestvirtualgoods.com/pricing)

## API integration examples

These minimal, text-only requests use the exact Y-API model ID. They do not demonstrate image, audio, video, file or tool support. The output limit also needs room for reasoning; an empty answer with finish_reason=length can mean the budget was exhausted.

Set the TOKEN environment variable to a key from your console. Run this on your server or locally; never expose a key in browser code or a public repository.

### A task to try

Route each incoming request to one of three queues based on the text, and explain in one sentence what triggered the choice.

```bash
curl --fail-with-body --silent --show-error --max-time 120 \
  'https://api.y-api.bestvirtualgoods.com/v1/chat/completions' \
  -H "Authorization: Bearer ${TOKEN:?Set TOKEN first}" \
  -H 'Content-Type: application/json' \
  --data-binary @- <<'JSON'
{
  "model": "openai/gpt-6-luna",
  "messages": [
    {
      "role": "user",
      "content": "Route each incoming request to one of three queues based on the text, and explain in one sentence what triggered the choice."
    }
  ],
  "max_tokens": 4096
}
JSON
```

```python
import json
import os
import sys
import urllib.error
import urllib.request

payload = {
  "model": "openai/gpt-6-luna",
  "messages": [
    {
      "role": "user",
      "content": "Route each incoming request to one of three queues based on the text, and explain in one sentence what triggered the choice."
    }
  ],
  "max_tokens": 4096
}

request = urllib.request.Request(
    "https://api.y-api.bestvirtualgoods.com/v1/chat/completions",
    data=json.dumps(payload).encode("utf-8"),
    headers={
        "Authorization": "Bearer " + os.environ["TOKEN"],
        "Content-Type": "application/json",
    },
    method="POST",
)
try:
    with urllib.request.urlopen(request, timeout=120) as response:
        result = json.load(response)
    print(json.dumps(result, ensure_ascii=False, indent=2))
except urllib.error.HTTPError as error:
    print(error.read().decode("utf-8"), file=sys.stderr)
    raise SystemExit(1)
```

### How to evaluate the result

Measure routing accuracy on a labeled sample and watch the cost per thousand requests, since the tiered pricing means the average rate depends on your request sizes.

## Before you choose

### How does Luna relate to GPT-6 Sol?

They are separate catalog entries with separate IDs and prices; Luna is the cheaper, faster tier. Switching between them is a model-field change, but the results are not interchangeable, so re-run your evaluation.

## Sources & scope

Technical facts come from the cited model page and, where available, its linked publisher card. A card describes that checkpoint; it is not proof of the weights a gateway serves. Prices come only from the Y-API catalog. We do not claim measured latency, uptime or benchmark scores for this endpoint.

- [OpenRouter model page & specifications](https://openrouter.ai/openai/gpt-6-luna)
- [Y-API catalog & prices (JSON)](https://y-api.bestvirtualgoods.com/models.json)

## Models to compare

Compare these alternatives on the same inputs. Their descriptions explain different roles; a lower price does not establish equivalent quality.

### [GPT-5.6 Luna](https://y-api.bestvirtualgoods.com/models/openai/gpt-5.6-luna)

GPT-5.6 Luna is the GPT-5.6 entry aimed at high-volume, latency-sensitive chat, classification and lightweight agent tasks. It is a separate cost-efficiency candidate, not a claim of Sol-equivalent reasoning at a lower price.

### [Claude Haiku 5.5](https://y-api.bestvirtualgoods.com/models/anthropic/claude-haiku-5.5)

Claude Haiku 5.5 is the current small, fast Claude model, aimed at high-volume and cost-sensitive work such as summarization, subagents and browser automation. It carries a 1M-token window at the lowest input price in the Claude lineup here.

## Links

- HTML version of this page: https://y-api.bestvirtualgoods.com/models/openai/gpt-6-luna
- Site index for agents: https://y-api.bestvirtualgoods.com/llms.txt
- Full reference (single file): https://y-api.bestvirtualgoods.com/llms-full.txt
- OpenAPI 3.1 spec: https://y-api.bestvirtualgoods.com/openapi.json
- Model catalog (JSON, no key needed): https://y-api.bestvirtualgoods.com/models.json
- API base URL: `https://api.y-api.bestvirtualgoods.com/v1`
- Contact: support@bestvirtualgoods.com
- Model catalog: https://y-api.bestvirtualgoods.com/models
- Integration guide: https://y-api.bestvirtualgoods.com/docs