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What is GPT-5.6 Sol?

GPT-5.6 Sol is a next-generation OpenAI model previewed as the flagship option in the GPT-5.6 family. The series includes Sol for the strongest capability, Terra for balanced everyday work, and Luna for faster, lower-cost use cases. GPT-5.6 Sol is built for demanding work across coding, agentic automation, biology, cybersecurity, research, and enterprise knowledge workflows. The model introduces a new max reasoning effort that allows it to spend more time reasoning through difficult problems. It also adds ultra mode, which coordinates subagents to help accelerate complex tasks that benefit from parallel or multi-agent execution. In coding workflows, GPT-5.6 Sol is designed for command-line tasks that require planning, iteration, testing, tool coordination, and long-horizon software engineering judgment. In biology workflows, it is positioned for genomics and quantitative-biology analysis where efficient reasoning over complex scientific tasks matters. In cybersecurity, GPT-5.6 Sol supports legitimate defensive work such as vulnerability discovery, patch development, debugging, security education, code review, and authorized testing. OpenAI describes GPT-5.6 Sol as more capable at helping users find and fix vulnerabilities than reliably carrying out end-to-end attacks under tested conditions. The model’s release is paired with a layered safeguard system that includes model-level refusals, real-time misuse classifiers, paused generation for higher-risk cases, account-level review, automated red-teaming, third-party testing, differentiated access, and enterprise safety controls. GPT-5.6 Sol helps developers, researchers, enterprises, and cyber defenders use frontier AI for advanced technical work while supporting safer deployment, stronger oversight, and phased access.

What is Abliterated Large V2?

Abliterated Large V2 is an advanced text-based reasoning model developed by Abliteration AI for cybersecurity analysis, autonomous AI agents, software development, and adversarial model evaluation. The model is based on Z.ai's GLM 5.3 architecture and has undergone weight-level modifications intended to reduce refusal behavior. This modification process, known as abliteration, changes internal model representations associated with rejecting certain requests rather than relying on prompt-based jailbreak techniques. Its one-million-token context window enables the processing of large software repositories, extensive technical documentation, security research materials, and long-running agent workflows. The model supports advanced code generation, debugging, technical reasoning, and multistep programming tasks requiring interaction with external tools. Cybersecurity applications include vulnerability analysis, authorized penetration testing, exploit research, security validation, and automated assessment of software weaknesses. AI safety researchers can use the model to evaluate agent behavior, test security boundaries, and examine how systems respond to adversarial scenarios. Native tool calling enables the model to interact with supported external applications, development environments, and automated testing infrastructure. Structured output functionality allows developers to generate machine-readable responses for integration with security tools and programmatic workflows. Abliterated Large V2 is hosted in FP8 precision and provides access through OpenAI-compatible chat completion and response endpoints, as well as an Anthropic-style messages interface. The model is available through Abliteration AI and third-party inference providers, with automatic prompt caching, configurable reasoning capabilities, and default zero-retention handling of API inputs and outputs.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Auggie CLI
CSS
ChatGPT Go
Claw Code
Codex Security
Databricks
Ghost
GitHub
Higgsfield Supercomputer
Kimi K2 Thinking
Microsoft 365 Copilot Chat
Microsoft Excel
Microsoft Foundry Models
Muse
OpenAI
R
SimpleClaw
Transor

API Availability

Has API

API Availability

Has API

Pricing Information

$4 per 1M tokens (input)
$4 input / $20 output per 1M tokens

Pricing Information

$3 per 1M tokens (input)
$3.00 per 1 million input tokens, $5.00 per 1 million output tokens, and $0.30 per 1 million cached input tokens

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

OpenAI

Date Founded

2015

Company Location

United States

Company Website

openai.com

Company Facts

Organization Name

Abliteration.ai

Date Founded

2025

Company Location

United States

Company Website

abliteration.ai/

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

AI Vision Models

Not specified

Large Language Models

Not specified

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

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