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OpenAI · Efficient

GPT 5.6 Luna

Added Jul 9, 2026

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Use in the app

GPT-5.6 Luna is the fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume chat, classification, lightweight agentic workflows, and latency-sensitive reasoning tasks.

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • PDF input
Input
Text, Images
Output
Text
Reasoning effort
none · low · medium · high · xhigh · max
Discovery tier
Efficient

Pricing

USD per 1M tokens
Input
$0.20
Output
$1.20
Cache read
$0.02
Cache write
$0.25

Reference prices as published by the model provider. API example

Specifications

Context window
1.1M
Max output
128K
Average output (7 days)
281 tokens
Longer than 29% of 465 models

Side by side

GPT 5.6 Luna compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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GPT 5.6 LunaOpenAIThis modelClaude Sonnet 5AnthropicRemove
ProviderOpenAIAnthropic
Discovery tierEfficientFrontier
AddedJul 9, 2026Jun 30, 2026
Limits
Context window1.05MBest1M
Max output128K128K
Average output281 tokens291 tokens
Pricing, USD per 1M tokens
Input$0.20Best$2.00
Output$1.20Best$10.00
Cache read$0.02Best$0.20
Cache write$0.25Best$2.50
Performance
Throughput297.5 tok/sBest107.7 tok/s
Time to first token4.6 sBest14.6 s
Request success (24h)99.9%99.9%
Benchmark indexes
Intelligence Index37.338.2Best
Coding Index71.471.5Best
Capabilities
ReasoningYesNo
ToolsYesYes
VisionYesYes
Structured outputYesYes
PDF inputYesYes
Reasoning effortnone, low, medium, high, xhigh, max—

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • GPT 5.6 Luna
  • Claude Sonnet 5

Intelligence Index

  • GPT 5.6 Luna37.3
  • Claude Sonnet 538.2

GPT 5.6 Luna tested at max reasoning effort

GPT 5.6 Luna: Better than 81% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GPT 5.6 Luna: 71.4
    • Claude Sonnet 5: 71.5Top

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GPT 5.6 Luna: 50.2%Top
    • Claude Sonnet 5: 36.5%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GPT 5.6 Luna: 18.6%Top
    • Claude Sonnet 5: 10.8%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GPT 5.6 Luna: 1,339 Elo
    • Claude Sonnet 5: 1,357 EloTop

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GPT 5.6 Luna: 1,460 Elo
    • Claude Sonnet 5: 1,464 EloTop

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GPT 5.6 Luna: 24.0%Top
    • Claude Sonnet 5: 13.2%

  • AA-LCRv1.1

    Reasoning across long documents

    • GPT 5.6 Luna: 83.7%Top
    • Claude Sonnet 5: 82.0%

  • MLCR-AA

    Long-context reasoning over medical records

    • GPT 5.6 Luna: 20.0%Top
    • Claude Sonnet 5: 5.0%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GPT 5.6 Luna: 39.5%
    • Claude Sonnet 5: 41.3%Top

  • GPQA Diamond

    Graduate-level science questions

    • GPT 5.6 Luna: 91.1%Top
    • Claude Sonnet 5: 91.1%Top

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GPT 5.6 Luna: 11.6%
    • Claude Sonnet 5: 14.1%Top

  • SciCode

    Scientific computing in Python

    • GPT 5.6 Luna: 53.6%
    • Claude Sonnet 5: 54.3%Top

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GPT 5.6 Luna: 83.7%Top
    • Claude Sonnet 5: 82.0%

Scores from Artificial Analysis, updated Oct 26, 2026. GPT 5.6 Luna was tested at max reasoning effort; compare scores measured at the same effort.Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Throughput
297.5 tok/s
Faster than 93% of 247 models
Time to first token
4.6 s
Quicker than 35% of 247 models
Prompt cache hits
85.5%
About $0.0462 per 1M input tokens with caching
Request success (24h)
99.9%
Reliable

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Hourly request success · last 72 hoursLowest hour 99.7%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-5.6-luna",
    "reasoning_effort": "medium",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="openai/gpt-5.6-luna",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

OpenAI

Other OpenAI models, starting with the same family.