GPT-6 Luna API — pricing & specs
GPT-6 Luna is an OpenAI text and image model with selectable reasoning effort and Responses function calling. On KeepRouter, GPT-6 Luna costs $0.2500 per 1M input tokens and $0.7500 per 1M output tokens, billed pay-as-you-go with no monthly fee. Call it through a compatible KeepRouter endpoint supported by its active route, with the model id gpt-6-luna.
| Maker | OpenAI |
|---|---|
| Modality | Text, vision |
| Context window | 1,050,000 tokens |
| Max output | 128,000 tokens |
| Knowledge cutoff | 2026-05-18 |
| Input price | $0.2500 per 1M tokens |
| Output price | $0.7500 per 1M tokens |
| Cached input | $0.0200 per 1M tokens |
| Capabilities | Vision (image input), Chat completions, Streaming where supported, Tool calling where supported |
| Endpoint | POST /v1/chat/completions or POST /v1/responses |
| Model id | gpt-6-luna |
How pricing works for GPT-6 Luna
GPT-6 Luna is billed per token — $0.2500 per 1M input tokens and $0.7500 per 1M output tokens, with cached input at $0.0200 per 1M tokens. The published price is pay-as-you-go, with no monthly fee; actual request cost depends on measured token usage.
Calling GPT-6 Luna on KeepRouter
Point a compatible client at the supported KeepRouter endpoint and set the model to gpt-6-luna. KeepRouter preserves the client-facing request shape while handling upstream routing or translation. Use POST /v1/chat/completions or, on compatible chat routes, POST /v1/messages; streaming and tool support depend on the model's active route.
cURL
curl https://keeprouter.com/v1/responses \
-H "Authorization: Bearer $KEEPROUTER_KEY" -H "Content-Type: application/json" \
-d '{"model":"gpt-6-luna","input":"Reply with one short greeting.","reasoning":{"effort":"low"},"max_output_tokens":1024,"store":false}'Python
import os
from openai import OpenAI
client = OpenAI(base_url="https://keeprouter.com/v1", api_key=os.environ["KEEPROUTER_KEY"], max_retries=0)
r = client.responses.create(model="gpt-6-luna", input="Reply with one short greeting.", reasoning={"effort": "low"}, max_output_tokens=1024, store=False)JavaScript
const res = await fetch("https://keeprouter.com/v1/responses", {
method: "POST",
headers: { Authorization: "Bearer " + process.env.KEEPROUTER_KEY, "Content-Type": "application/json" },
body: JSON.stringify({"model":"gpt-6-luna","input":"Reply with one short greeting.","reasoning":{"effort":"low"},"max_output_tokens":1024,"store":false}),
});Estimate API costs
At the current KeepRouter customer price, an example workload of 1,000 total input tokens, no cached input, and 500 output tokens per request costs approximately $0.000625 per request. At 100 requests per day, that is $1.88 over 30 days. This is a usage estimate, excluding processing fees, taxes, retries and application infrastructure. Actual usage, cache hits and supported generation durations need their own checks.
Adjust quantities in the API cost calculator.
Model identity and official sources
Sources checked 2026-10-03.
Bounded generation checked
On October 3, 2026, this exact ID returned HTTP 200, visible text and final token usage through /v1/responses. These small checks do not establish task accuracy, full-context capacity, media compatibility or sustained throughput.
Model and evaluation task
Evaluate coding changes against the same repository tests, including a multi-step tool conversation. Sol and Luna have different prices; compare cost per accepted change rather than cost per token alone.
API contract and migration
Use Responses for reasoning with tools. Chat Completions tools require reasoning_effort=none. The copyable example uses Responses and a bounded output budget.
Customer price and verification scope
The live prices above are KeepRouter customer rates. One fixed input rate covers ordinary input and the supported cache-write or long-context ceiling; no extra cache-write fee is added. Cache hits use the separate cached-input rate. These are not the maker's short-context base prices. Maker specifications and catalog checks do not certify every generation workflow.
KeepRouter · pricing and usage · KeepRouter · workload calculator
How to evaluate GPT-6 Luna
GPT-6 Luna is listed on KeepRouter as text, vision under the exact id gpt-6-luna. Use /v1/responses for the listed route; a maker's upstream features do not automatically apply to this gateway endpoint. The published context window is 1,050,000 tokens and the published output limit is 128,000 tokens. These are limits, not a recommended request size.
First workload: Start with a text question plus one representative image, then repeat the same question with text only. Compare answer quality, latency and billed input/output tokens.
Before production: For agent use, test tool calls and structured output on this exact model route before production; an OpenAI-compatible chat endpoint alone does not prove either feature.
Agent setup paths
OpenAI SDK (Responses)
Use the SDK's responses.create operation with the exact model gpt-6-luna. In an agent product, select an adapter that emits /v1/responses; a Chat Completions configuration is not an equivalent tool integration. Preserve complete returned conversation items between tool turns. Official setup.
import os
from openai import OpenAI
client = OpenAI(base_url="https://keeprouter.com/v1", api_key=os.environ["KEEPROUTER_KEY"], max_retries=0)
r = client.responses.create(model="gpt-6-luna", input="Reply with one short greeting.", reasoning={"effort": "low"}, max_output_tokens=1024, store=False)These are documented configuration paths; model-specific tool, streaming and multimodal behavior still needs a real request test.
Public model usage evidence
No public, exact-variant usage figure has been verified for this KeepRouter model id. Missing data is not zero usage; family-level or maker-wide traffic is not presented as this model's traffic.
Published examples and cases
No exact-model customer case has been verified for this entry. The workload above is an evaluation recipe, not a claim of a public deployment.
Source and verification boundary
Official GPT-6 Luna documentation. KeepRouter's live catalog is authoritative for the customer price and enabled endpoint shown here; the maker remains authoritative for upstream model capabilities and limits.
Pricing and implementation guides
- GPT-6.1 Sol: Responses, tools and pricing
- GPT API pricing and SDK migration
- Calculate your API workload cost
- KeepRouter API keys: move from free to paid models
Guides
Related models
- GPT-6 Sol by OpenAI — $5.00 per 1M input tokens and $15.00 per 1M output tokens
- GPT-6 Astra by OpenAI — $25.00 per 1M input tokens and $75.00 per 1M output tokens
- GPT-6.1 Sol by OpenAI — $5.00 per 1M input tokens and $15.00 per 1M output tokens
- GPT-5.5 by OpenAI — $5.00 per 1M input tokens and $30.00 per 1M output tokens
- GPT Image 1.5 by OpenAI — $8.00 per 1M input tokens and $32.00 per 1M output tokens
- GPT-4o by OpenAI — $2.50 per 1M input tokens and $10.00 per 1M output tokens
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Catalog facts and prices last changed .
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