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Description

GPT-5.6 Luna is OpenAI’s fast, cost-efficient model in the GPT-5.6 lineup. The GPT-5.6 family includes Sol for flagship performance, Terra for balanced everyday work, and Luna for strong capability at the lowest listed price. Luna is designed for users who need scalable AI support for routine tasks, coding assistance, workflow automation, analysis, and production API use cases where speed and cost matter. According to the pasted preview text, Luna is priced below both Sol and Terra, making it the most affordable GPT-5.6 option for high-volume workloads. The model is included in GPT-5.6 benchmark previews across Terminal-Bench 2.1, GeneBench v1, ExploitBench, and ExploitGym, showing that it is part of the same technical family used for coding, biology, and cybersecurity evaluations. Luna benefits from safeguards developed across the GPT-5.6 series, including model-level refusal training, real-time cyber and biology misuse classifiers, account-level signals, differentiated access, monitoring, enforcement, and ongoing testing. These controls are designed to preserve legitimate use cases such as debugging, code review, defensive testing, security education, and productivity automation while constraining prohibited misuse. GPT-5.6 Luna is planned for broader access through ChatGPT, Codex, and the API after the limited preview period. GPT-5.6 Luna helps developers and organizations run useful AI workflows with a practical balance of affordability, responsiveness, and safety.

Description

K2 Horizon comprises a network of six open models, including the 375B-A23B, 36B-A4B, 32B, 7B, 3.7B, and 0.9B, all engineered to excel in various domains such as reasoning, mathematics, coding, agentic tasks, and overall capabilities. These models share a unified architecture, vocabulary, training techniques, interfaces, evaluation frameworks, and deployment tools, facilitating seamless transitions between sizes and dynamic workload management. The fleet's flagship, the 375B-A23B model, is particularly adept at handling intricate reasoning, software development, research projects, and long-term agentic functions, while the 32B and 36B-A4B models focus on delivering robust local deployment solutions. Notably, the 36B-A4B model features an innovative Mixture-of-Value Attention mechanism, which merges sparse attention with Mixture-of-Experts layers, allowing it to engage approximately 4 billion parameters per token and compete closely with the performance of the denser 32B model. This architecture not only enhances flexibility but also maximizes resource efficiency across a wide range of applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

.NET
Amazon Bedrock
Augment Code
Brokk
C++
ChatGPT Plus
ChatGPT Work
Cosmos
Dessix
GPT-5.1-Codex
LobeHub
Microsoft 365
Muse
Node.js
OpenTag
R
React
Ruby
Swift
Use AI

Integrations

.NET
Amazon Bedrock
Augment Code
Brokk
C++
ChatGPT Plus
ChatGPT Work
Cosmos
Dessix
GPT-5.1-Codex
LobeHub
Microsoft 365
Muse
Node.js
OpenTag
R
React
Ruby
Swift
Use AI

Pricing Details

$0.20 per 1M tokens (input)
$0.20 input / $1.20 output per 1 million tokens
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

OpenAI

Founded

2015

Country

United States

Website

openai.com

Vendor Details

Company Name

Institute of Foundation Models

Founded

2025

Country

United States

Website

ifm.ai/blog/k2/

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