OpenAI

OpenAI

GPT-5.6 Luna Pro

Luna at the same list price with the Pro serving profile. 1.05M context, vision, file input; the rate doubles above 272K prompt tokens.

Modalities

Text+Image → Text

Below release

Not established

Weights

Not published

Where it sits in the catalogue Kyma measures

Every number against every text model Kyma prices per token — a stated rule, not a chosen line-up.

Price · input#13/69

$0.27

output $1.62 · cached $0.027

median $1.009 · best $0.0494

Price · output#23/69

$1.62

per 1M tokens generated

median $3.528 · best $0.2164

Availability · 30d#56/68

87.05%

471 observations since 2026-08-01

median 93.2% · best 100.0%

Throughput#12/67

74.7 tok/s

probe median, one fixed prompt

median 39.7 tok/s · best 324.4 tok/s

Response time#45/67

3.08 s

probe median, to a complete answer

median 2.54 s · best 0.86 s

Context

1.05M

max output 128,000

published by OpenAI, not measured here

Tick above each rail is this model, below it the other 68. Dashed rule is the field median, solid is its best. Better is left; the axis stops at the 90th percentile, so a few models sit past its right edge.

Usage

How much this model is actually called here.

Rank

#31

of 98 active models

Tokens served

12.4M

all-time

Platform share

0.3%

of all tokens

Tokens · last 15 daysSep 1Sep 15

Two clocks, and why they disagree

Kyma measures this model twice. Both are real; they answer different questions.

Probe · every 6h · 30 days

3.08s to answer

One fixed prompt, on a schedule, to every model. Comparable, because the model is the only thing that changes.

Observations
471
Answered by a substitute
34

Real traffic · last 7 days

3.59s to answer

Your requests, at the lengths clients actually send. Not comparable between models, but it is what running this one feels like.

Requests
67
Completed
100%
p95
58.9 s

Caching, as realised · last 7 days

3.9% of input cached

The share of input that actually hit cache, so the effective rate below is what was charged, not a best case.

Cached input
6.5K
Fresh input
162.4K
List input
$0.27 /1M
Effective input
$0.260609 /1M

The gap is prompt length, not the model degrading. Use the probe figure to choose between models, the traffic figure to budget for your own.

Pricing

Pay per token. Cached input bills at this model’s own cached rate, listed below.

$0.27 /1M input$1.62 /1M output
Hobby10 req/day · 2K in / 500 out
~$0.40/mo
Production1,000 req/day · 2K in / 500 out
~$40.50/mo
Scale20,000 req/day · 2K in / 500 out
~$810/mo
+ Estimate your workload
1,000
2,000
500
30%

Estimated monthly cost

$36.13

$1.20 / day on GPT-5.6 Luna Pro

Same workload on:

GPT-5.6 Sol Pro$365+909%
GPT-5.6 Sol$365+909%

Estimates use list pricing with cached input at this model's own cached rate. Actual bills depend on real token counts, and every response includes its exact cost.

How it compares

Against the peers people actually weigh it against.

SpecGPT-5.6 Luna ProGPT-5.6 Sol ProGPT-5.6 Sol
Input /1M$0.27$2.70$2.70
Output /1M$1.62$13.50$13.50
Context1M1M1M
ToolsYesYesYes
ReasoningYesYesYes
Throughput74.7 tok/s54.6 tok/s28.8 tok/s

Quick start

Up and running in under two minutes.

  1. 1

    Create an API key

    Sign up and grab a key from the dashboard — $0.50 free credit on the free tier, which covers GPT-5.6 Luna Pro. No card required.

    Get API key →
  2. 2

    Make your first request

    Drop in your key and send a chat completion — fully OpenAI-compatible.

    curl https://kymaapi.com/v1/chat/completions \
      -H "Authorization: Bearer YOUR_API_KEY" \
      -H "Content-Type: application/json" \
      -d '{
        "model": "gpt-5.6-luna-pro",
        "messages": [
          {"role": "user", "content": "Explain prompt caching in one paragraph."}
        ]
      }'
  3. 3

    Stream responses

    Add "stream": true to receive tokens as they arrive.

    curl https://kymaapi.com/v1/chat/completions \
      -H "Authorization: Bearer YOUR_API_KEY" \
      -H "Content-Type: application/json" \
      -d '{
        "model": "gpt-5.6-luna-pro",
        "stream": true,
        "messages": [{"role": "user", "content": "Hello!"}]
      }'

FAQ

Common questions about this model.

What is the context window of GPT-5.6 Luna Pro?

GPT-5.6 Luna Pro has a 1M-token context window — roughly 1544 pages of text in a single request.

How much does the GPT-5.6 Luna Pro API cost?

$0.27 per 1M input tokens and $1.62 per 1M output tokens, with cached input at $0.027/1M — 90% off the input rate on repeated prompt prefixes. No subscription; you pay only for what you use.

Does GPT-5.6 Luna Pro support function calling?

Yes — GPT-5.6 Luna Pro supports tool/function calling and structured outputs (JSON mode), so it works with agent frameworks out of the box.

Are the weights for GPT-5.6 Luna Pro publicly available?

No. OpenAI does not publish GPT-5.6 Luna Pro's weights — it is reachable through an API rather than as a file you can download and run (https://huggingface.co/openai, read 2026-08-14). That is OpenAI's decision about their own product, not a limitation of Kyma.

Is GPT-5.6 Luna Pro ever served below the precision its creator released it at?

Kyma cannot say, and for this model nobody can. OpenAI does not publish GPT-5.6 Luna Pro's weights, so there is no released checkpoint whose precision a route could be measured against. We publish "not established" rather than reading a low format as a downgrade: on several models in this catalogue a low format is exactly how the creator ships it.

How do I use GPT-5.6 Luna Pro?

Kyma is OpenAI-compatible: point your SDK's base URL at https://kymaapi.com/v1, use your Kyma API key, and set the model to gpt-5.6-luna-pro. Signing up is free and includes $0.50 of credit on the free tier, which covers this model — no card required.

Start with $0.50 free credit on the free tier — no card required.Create account →

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