# GPT-5.6 Luna — API, capabilities & pricing | Y-API

> 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.

This is the markdown representation of https://y-api.bestvirtualgoods.com/models/openai/gpt-5.6-luna. Generated by `scripts/generate-seo-assets.mjs` from the same copy the page renders — do not edit by hand.

Model ID: `openai/gpt-5.6-luna`

Sources reviewed: 2026-10-04. Y-API catalog snapshot: 2026-10-04.

## Choosing this model

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

### Where to start

Start with bounded tasks such as intent classification and extracting a small set of fields. Route ambiguous or high-impact cases to review instead of making a cheap model responsible for every decision.

### What to watch for

Model positioning is not a Y-API latency measurement. Structured-output support in the reference also does not remove the need for schema validation, unknown-value handling and an escalation path.

## 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 | 2026-07-09 |
| Parameters listed by OpenRouter | `include_reasoning`, `max_completion_tokens`, `max_tokens`, `reasoning`, `reasoning_effort`, `response_format`, `seed`, `structured_outputs`, `tool_choice`, `tools`, `verbosity` |

## Estimate your cost

| Price basis | Input / 1M tokens | Output / 1M tokens |
| --- | --- | --- |
| Account credit | $0.30 | $1.30 |
| Cash equivalent | $0.03 | $0.13 |

$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: $0.95. Estimated cash equivalent: $0.095.

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-5.6 Luna](https://y-api.bestvirtualgoods.com/models/openai/gpt-5.6-luna) | $0.95 | $0.095 |
| [GPT-5.6 Sol](https://y-api.bestvirtualgoods.com/models/openai/gpt-5.6-sol) | $20.00 | $2.00 |
| [Qwen3.8 Flash](https://y-api.bestvirtualgoods.com/models/qwen/qwen3.8-flash) | $0.45 | $0.045 |

## Use the API

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

Extract order_id and intent as JSON from: Please cancel order A-1042 before it ships. Use only information present in the sentence.

```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-5.6-luna",
  "messages": [
    {
      "role": "user",
      "content": "Extract order_id and intent as JSON from: Please cancel order A-1042 before it ships. Use only information present in the sentence."
    }
  ],
  "max_tokens": 4096
}
JSON
```

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

payload = {
  "model": "openai/gpt-5.6-luna",
  "messages": [
    {
      "role": "user",
      "content": "Extract order_id and intent as JSON from: Please cancel order A-1042 before it ships. Use only information present in the sentence."
    }
  ],
  "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

Validate the two fields and the order ID, then test missing IDs, multiple orders and ambiguous intent. Measure false confident extractions separately from parse failures.

## Before you choose

### When should a Luna workflow escalate to Sol?

Define thresholds from your own evaluations: conflicting evidence, repeated validation failure or a task with substantial reasoning depth. Do not use the model’s self-reported confidence as the sole trigger.

## 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-5.6-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 Sol](https://y-api.bestvirtualgoods.com/models/openai/gpt-5.6-sol)

GPT-5.6 Sol is the flagship entry of the GPT-5.6 family in OpenRouter’s catalog. Its stated focus is complex reasoning, command-line coding and multi-step problem solving, with text, image and file inputs listed in the reference.

### [Qwen3.8 Flash](https://y-api.bestvirtualgoods.com/models/qwen/qwen3.8-flash)

Qwen3.8 Flash is Alibaba’s multimodal reasoning entry for text, images and video in the OpenRouter catalog. It brings document and chart understanding into the same model selection as coding assistance and long-context analysis.

## Links

- HTML version of this page: https://y-api.bestvirtualgoods.com/models/openai/gpt-5.6-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