OpenAI: GPT-5.6 Luna
Try GPT-5.6 Luna for free in your browser, and add it to your app for free with Puter.js AI API.
Try it free Add to your app// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "openai/gpt-5.6-luna"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "openai/gpt-5.6-luna"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
Model Card
GPT-5.6 Luna is OpenAI's smallest and most cost-efficient model in the GPT-5.6 family, positioned below GPT-5.6 Terra and the flagship GPT-5.6 Sol. It targets high-volume, cost-sensitive workloads such as customer service automation, content moderation, and data extraction, where lower per-token cost matters more than peak capability.
It shares the same 1,050,000-token context window, 128,000 max output tokens, and February 16, 2026 knowledge cutoff as its larger siblings. Luna accepts text and image input, produces text output, and supports function calling, structured outputs, streaming, and reasoning tokens, along with tool access including web search, file search, code interpreter, computer use, and MCP.
At $1 per million input tokens and $6 per million output tokens, Luna costs 60% less on input than GPT-5.6 Terra, making it suited for applications that run at scale rather than tasks requiring the highest accuracy.
Context Window 1M
tokens
Max Output 128K
tokens
Input Cost $0.2
per million tokens
Output Cost $1.2
per million tokens
Input text, image
modalities
Tool Use Yes
Knowledge Cutoff Feb 16, 2026
Release Date Jul 9, 2026
Try GPT-5.6 Luna for free
Try GPT-5.6 Luna instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How GPT-5.6 Luna performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 91.1% |
| Humanity's Last Exam Cross-domain reasoning | 39.5% |
| SciCode Scientific programming | 53.6% |
| LCR Long-context reasoning | 83.7% |
Scores sourced from Artificial Analysis.
Find other OpenAI models →
GPT-6.1 Sol
GPT-6.1 Sol is OpenAI's mid-tier model in the GPT-6 family, released September 29, 2026 as an update to GPT-6 Sol. It sits below the flagship GPT-6 Astra, takes text and image input, supports tool calling, and has a 1,050,000-token context window with 128,000 max output tokens. Pricing is unchanged from GPT-6 Sol at $2 per million input tokens and $10 per million output tokens, while scores are higher. It reaches 75.2% on DeepSWE 1.1 (68.8% for GPT-6 Sol), 71.4% on OSWorld 2.0 (64.4%), and 32.0% on GDP.pdf (28.0%). Its factual error rate at low reasoning effort fell from 11.4% to 7.7%. In one third-party comparison table, GPT-6 Astra scores 74.8% on DeepSWE and 73.5% on OSWorld at roughly five times the price. GPT-6.1 Sol suits coding agents, computer use, document question answering, and workflow automation where cost per task matters.
ChatGPT-6.1 Sol Pro
GPT-6.1 Sol Pro is OpenAI's higher-effort configuration of GPT-6.1 Sol, the mid-tier model in the GPT-6 family. Based on how OpenAI handled GPT-6 Sol Pro, it is likely the same underlying model with reasoning mode set to pro, though OpenAI's documentation for the 6.1 release does not confirm this. It has a 1,050,000-token context window and 128,000 max output tokens, at $2 per million input tokens and $10 per million output tokens. Supported parameters include reasoning effort, tools, tool choice, structured response formats, seed, and streaming. Sol Pro is intended for complex requests such as agentic coding, computer use, and workflow automation, where answer quality matters more than latency. We found no published benchmarks for the Pro configuration itself.
ChatGPT-6 Sol
GPT-6 Sol is OpenAI's mid-tier model in the GPT-6 family, released September 22, 2026 as a faster, cheaper counterpart to the flagship GPT-6 Astra, built on the same training methods. OpenAI positions it for complex development work that developers run repeatedly, such as building features, reviewing code, debugging, and analyzing data. OpenAI reports Sol scoring 68.8% on the DeepSWE 1.1 coding benchmark, 60.5% on OSWorld 2.0 for computer use at xhigh effort, and 56.4% on Agents' Last Exam, a test of professional work across 55 sub-industries. The company says Sol makes about half as many factual errors as GPT-5.6 Sol, approaching Astra-level reliability at a lower cost. At $2 per million input tokens and $10 per million output tokens, half of GPT-5.6 Sol's rate, Sol matches Claude Sonnet 5's standard pricing, though no published benchmark compares the two models directly.
Frequently Asked Questions
You can access GPT-5.6 Luna by OpenAI through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
GPT-5.6 Luna is free to try with a Puter account. Every account includes a free AI allowance, and you can chat with it in the playground on this page. You can upgrade your account anytime for a larger allowance.
GPT-5.6 Luna is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.
| Price per 1M tokens | |
|---|---|
| Input | $0.2 |
| Output | $1.2 |
GPT-5.6 Luna was created by OpenAI and released on Jul 9, 2026.
GPT-5.6 Luna supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,100 pages of text.
GPT-5.6 Luna can generate up to 128K tokens in a single response.
GPT-5.6 Luna has a knowledge cutoff date of Feb 16, 2026. This means the model was trained on data available up to that date.
GPT-5.6 Luna accepts the following input types: text, image. It produces: text.
Yes, GPT-5.6 Luna supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
GPT-5.6 Luna scores 37.3 on the Artificial Analysis Intelligence Index, outperforming 88% of tracked models. On coding, it scores 71.4 (outperforms 82% of models).
Yes — the GPT-5.6 Luna API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Add GPT-5.6 Luna to your app for free
Developers can integrate GPT-5.6 Luna for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.