OpenAI
GPT-6.1 Sol
gpt-6.1-sol
Total Context
1.1M
Max Output
128K
Released
N/A
Input$2 / M tokens
Output$10 / M tokens
GPT-5.6 Luna
gpt-5.6-lunaGPT-5.6 Luna is the general-purpose version of the Luna series, suitable for everyday AI applications. It can be used for chat Q&A, text rewriting, summarization, information extraction, simple reasoning, coding assistance, and office automation. Luna is a practical choice for prototypes, lightweight business features, batch content processing, and common user interaction scenarios. It is a good starting model when speed, simplicity, and cost control are important, while Luna Pro can be considered for tasks that require higher-quality or more stable outputs.
Context Window
1.1M tokens
Maximum Output
128K tokens
Release Date
Jul 9, 2026
Modalities
GPT-5.6 Luna Pricing
| Token Tier | Input Price | Output Price | Cache Read | Cache Create 5m |
|---|---|---|---|---|
| <=272K | $1/M | $6/M | $0.1/M | $1.25/M |
| >272K | $2/M | $9/M | $0.2/M | $2.5/M |
GPT-5.6 Luna API Capabilities
Reasoning
Supported
Tool calling
Supported
Temperature parameter
Not supported
Attachments
Supported
Knowledge Base
2026-02-16
Endpoint Protocols
Completions API
GPT-5.6 Luna Model Highlights
GPT-5.6 Luna prioritizes economical, high-volume processing while retaining configurable reasoning, image understanding and a million-token context window.
High-Volume Efficiency
The model is designed for cost-sensitive workloads that process frequent requests or large collections of routine content.
Adjustable Reasoning
Reasoning effort can range from none through max, allowing lightweight and more analytical requests to use the same model family.
Long Multimodal Context
Text and image inputs can be processed within a 1,050,000-token context window, reducing the need to split large workloads.
GPT-5.6 Luna Use Cases
GPT-5.6 Luna is suited to high-volume classification, summarization and multimodal extraction where operating efficiency is important.
High-Volume Classification
Assign categories, priorities or routing labels to large streams of messages and documents for automated processing.
Long-Content Summarization
Condense long reports, support histories or document collections into concise summaries and action-oriented key points.
Multimodal Data Extraction
Extract routine fields and findings from text, screenshots, charts or scanned pages for indexing and downstream workflows.
How to Use GPT-5.6 Luna via the TokenHub API
import OpenAI from "openai"
const client = new OpenAI({
apiKey: process.env.TOKENHUB_API_KEY,
baseURL: "https://us-api.tokenhub.com/v1",
})
const result = await client.chat.completions.create({})
console.log(result.choices[0]?.message?.content)GPT-5.6 Luna Benchmarks
| Index score | ||
|---|---|---|
| Artificial Analysis Intelligence Index | Artificial Analysis broad capability aggregate | 33.3 |
| Artificial Analysis Coding Index | Artificial Analysis software task aggregate | 44.2 |
| Knowledge & Reasoning | ||
| GPQA | Advanced science problem solving | 83.5% |
| HLE | Broad expert-level exam set | 18.8% |
| Coding & Engineering | ||
| SciCode | Scientific coding challenges | 45.6% |
| Instruction Following & Agent Tasks | ||
| AA-LCR | Long-context reasoning | 59.3% |
Metrics sourced from Artificial Analysis
GPT-5.6 Luna FAQs
Common questions about using GPT-5.6 Luna on TokenHub.
What is GPT-5.6 Luna?+
GPT-5.6 Luna is a GPT-5.6 Luna-series model exposed through TokenHub. It is intended for users who need a general AI model for chat, reasoning, writing and API-based workflows.
What is GPT-5.6 Luna best for?+
It is suitable for conversational assistants, content drafting, summarization, structured data extraction, code help and multi-step task automation.
What are the strengths of GPT-5.6 Luna?+
Its strengths are general-purpose task coverage, clear instruction following and flexible integration through TokenHub. The standard version is generally a practical choice for everyday usage, quick iteration and cost-conscious workloads.
What limitations or tradeoffs should I consider with GPT-5.6 Luna?+
As with any AI model, review important outputs for accuracy, test prompts with your own data and compare latency, cost and quality against alternatives before production use.
How do I use GPT-5.6 Luna through the TokenHub API?+
Select "GPT-5.6 Luna" as the model in your TokenHub request, use your account endpoint and credentials, and set parameters such as temperature, max tokens and streaming according to your application needs.
How should I choose between GPT-5.6 Luna and related GPT-5.6 models?+
Start with a small evaluation set that reflects your real tasks. Choose the model that gives the best balance of answer quality, reliability, latency and cost for your workload.
Ready to use GPT-5.6 Luna?
Use one API key to access GPT-5.6 Luna and more AI models through TokenHub.