Abliterated Large V2

Abliterated Large V2

Abliteration.ai
GLM-5.3

GLM-5.3

Z.ai
+
+

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About

Abliterated Large V2 is a large language model developed by Abliteration AI for advanced reasoning, cybersecurity research, AI red teaming, and autonomous agent workflows. Based on Z.ai's GLM 5.3 architecture, the model uses weight-level modifications designed to reduce refusal behavior while preserving coding and reasoning capabilities. It supports a one-million-token context window, enabling analysis of extensive source code repositories, technical documentation, and lengthy task histories. The model is optimized for security research, vulnerability analysis, exploit testing, and complex software engineering tasks. Its capabilities include tool calling, structured outputs, configurable reasoning, and integration with external applications through compatible APIs. Abliterated Large V2 is available as a hosted text-only model through Abliteration AI and supported third-party AI inference providers.

About

GLM-5.3 is Z.ai’s frontier coding model designed for complex software engineering, long-horizon agent tasks, and advanced post-training research. The model uses the same base model as GLM-5.2, with improvements coming from scaled post-training across more environments, more diverse tasks, and larger compute investment. GLM-5.3 delivers stronger coding performance, better task ownership, improved benchmark results, and greater efficiency across realistic development workflows. It is built to handle complex coding tasks, production-style engineering work, research environments, automation tasks, and agentic workflows that require multi-step execution. The model also shows emergent cyber capabilities in vulnerability discovery and exploitation-chain reasoning, with safety evaluation and hardening planned before open-weight release.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Cybersecurity researchers, penetration testers, red teams, security engineers, AI safety researchers, software developers, autonomous agent builders, vulnerability researchers, and organizations seeking advanced reasoning, security testing, reduced-refusal AI models, and tool-integrated technical automation

Audience

Software engineers, coding agent builders, AI researchers, ML infrastructure teams, security researchers, developer tool teams, automation teams, technical leaders, and organizations that need frontier coding models, long-horizon reasoning, production-style software engineering, benchmark-driven model evaluation, reinforcement learning research, coding-agent integrations, reasoning effort controls, ZCode workflows, and advanced technical task automation

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$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
Free Version Not Supported
Free Trial Not Supported

Pricing

Free
Open source
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5

Pros & Cons from Real Users

Pros

  • The thing I like most is that GLM-5.3 feels aimed at serious engineering work, not casual prompting. It is built around coding agents, long-running software tasks, debugging, and the kind of multi-step execution that actually matters when you are working inside real repos. The post-training jump is also interesting. Z.ai is not just talking about a bigger model; it is pushing the idea that better training on agentic coding and cyber workflows can make the model more useful in practice.

Cons

  • The cybersecurity angle is impressive, but it is also where I would be most cautious. Strong vulnerability discovery and cyber reasoning can be useful for defense, audits, and secure engineering, but I would want very clear controls around how it is used.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Abliteration.ai
Founded: 2025
United States
abliteration.ai/

Company Information

Z.ai
Founded: 2023
China
z.ai/

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Categories

AI Models Supported

Categories

Integrations

Amp Not Supported
C Not Supported
Cheaper Inference Not Supported
Cherry Studio Not Supported
Claude Code Not Supported
Cline Not Supported
Dessix Not Supported
GLM Coding Plan Not Supported
Hermes Agent Not Supported
LM Studio Not Supported
OpenRouter Not Supported
PyTorch Not Supported
Qoder Not Supported
Roo Code Not Supported
Rust Not Supported
Sup AI Not Supported
Swift Not Supported
TypeScript Not Supported
Venice.ai Supported
scikit-learn Not Supported

Integrations

Amp Supported
C Supported
Cheaper Inference Supported
Cherry Studio Supported
Claude Code Supported
Cline Supported
Dessix Supported
GLM Coding Plan Supported
Hermes Agent Supported
LM Studio Supported
OpenRouter Supported
PyTorch Supported
Qoder Supported
Roo Code Supported
Rust Supported
Sup AI Supported
Swift Supported
TypeScript Supported
Venice.ai Not Supported
scikit-learn Supported
Claim Abliterated Large V2 and update features and information
Claim Abliterated Large V2 and update features and information
Claim GLM-5.3 and update features and information
Claim GLM-5.3 and update features and information