OpenAI · Efficient
GPT 5.6 Luna Pro
GPT-5.6 Luna with Pro reasoning mode. Pro mode performs more model work for difficult tasks; reasoning effort remains independently configurable and defaults to medium.
- 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)
- 1.5K tokens
- Longer than 87% of 465 models
Side by side
GPT 5.6 Luna Pro compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GPT 5.6 Luna ProOpenAIThis model | GPT 6.1 Sol ProOpenAIRemove | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Discovery tier | Efficient | Frontier |
| Added | Jul 9, 2026 | Sep 29, 2026 |
| Limits | ||
| Context window | 1.05M | 1.05M |
| Max output | 128K | 128K |
| Average output | 1.5K tokens | 1.2K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.20Best | $2.00 |
| Output | $1.20Best | $10.00 |
| Cache read | $0.02Best | $0.10 |
| Cache write | $0.25Best | $2.50 |
| Performance | ||
| Throughput | 949.8 tok/s | — |
| Time to first token | 9.6 s | — |
| Request success (24h) | 99.8% | 100.0%Best |
| Benchmark indexes | ||
| Intelligence Index | 37.3 | — |
| Coding Index | 71.4 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Structured output | Yes | Yes |
| PDF input | Yes | Yes |
| Reasoning effort | none, low, medium, high, xhigh, max | 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 Pro
- GPT 6.1 Sol Pro
Intelligence Index
- GPT 5.6 Luna Pro37.3
- GPT 6.1 Sol Pro—
GPT 5.6 Luna Pro tested at max reasoning effort
GPT 5.6 Luna Pro: Better than 81% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- GPT 5.6 Luna Pro: 71.4
- GPT 6.1 Sol Pro: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- GPT 5.6 Luna Pro: 50.2%
- GPT 6.1 Sol Pro: —
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- GPT 5.6 Luna Pro: 18.6%
- GPT 6.1 Sol Pro: —
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- GPT 5.6 Luna Pro: 1,339 Elo
- GPT 6.1 Sol Pro: —
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- GPT 5.6 Luna Pro: 1,460 Elo
- GPT 6.1 Sol Pro: —
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- GPT 5.6 Luna Pro: 24.0%
- GPT 6.1 Sol Pro: —
AA-LCRv1.1
Reasoning across long documents
- GPT 5.6 Luna Pro: 83.7%
- GPT 6.1 Sol Pro: —
MLCR-AA
Long-context reasoning over medical records
- GPT 5.6 Luna Pro: 20.0%
- GPT 6.1 Sol Pro: —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GPT 5.6 Luna Pro: 39.5%
- GPT 6.1 Sol Pro: —
GPQA Diamond
Graduate-level science questions
- GPT 5.6 Luna Pro: 91.1%
- GPT 6.1 Sol Pro: —
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- GPT 5.6 Luna Pro: 11.6%
- GPT 6.1 Sol Pro: —
SciCode
Scientific computing in Python
- GPT 5.6 Luna Pro: 53.6%
- GPT 6.1 Sol Pro: —
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GPT 5.6 Luna Pro: 83.7%
- GPT 6.1 Sol Pro: —
Scores from Artificial Analysis, updated Oct 26, 2026. GPT 5.6 Luna Pro 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
- 949.8 tok/s
- Faster than 99% of 247 models
- Time to first token
- 9.6 s
- Quicker than 10% of 247 models
- Prompt cache hits
- 80.7%
- About $0.0548 per 1M input tokens with caching
- Request success (24h)
- 99.8%
- 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.
- 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.
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-pro",
"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-pro",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)OpenAI
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