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Description

Abliterated Large V2 is a large language model developed by Abliteration AI for cybersecurity research, software engineering, and complex autonomous AI agent tasks. The model is derived from GLM 5.3 and uses a process known as abliteration to modify neural network weights associated with refusal behavior. This approach is intended to reduce content restrictions that can interfere with authorized security assessments, adversarial testing, and technical research. Its one-million-token context window supports processing large codebases, extensive technical documents, and multistep agent execution histories. The model provides advanced reasoning capabilities for programming, debugging, vulnerability reproduction, and technical problem-solving. Its cybersecurity applications include penetration testing research, security control evaluation, AI red teaming, and vulnerability validation in authorized environments. Native function calling and structured output capabilities allow developers to integrate the model with automated tools and external systems. Abliterated Large V2 is hosted using FP8 numerical precision and supports OpenAI-compatible and Anthropic-style API interfaces. The platform also provides automatic prompt caching and a zero-data-retention policy for API prompts and responses by default.

Description

GLM-5.3 is Z.ai’s advanced coding and agentic reasoning model built through scaled post-training on top of the GLM-5.2 base model. The release focuses on frontier coding, long-horizon software engineering, agent tasks, cyber evaluation, and reinforcement learning at scale. GLM-5.3 improves significantly over GLM-5.2 on complex coding benchmarks, real-world engineering environments, Terminal Bench 3.0, DeepSWE, Agents’ Last Exam, and Z.ai’s internal Code Bench. The model is trained on environments that resemble real professional work, including tasks involving codebases, infrastructure, documentation, compute clusters, experiments, bottleneck diagnosis, implementation, testing, and measurable optimization. Z.ai’s post-training stack includes IndexShare for efficient long-context processing, SAO for reinforcement learning on long-horizon tasks, and slime for large-scale asynchronous training. GLM-5.3 supports three thinking effort levels, including low, high, and max, with max recommended for coding tasks. The model also demonstrates emergent cyber capabilities across vulnerability discovery and exploitation benchmarks, prompting continued safety evaluation and hardening before weights are released. GLM-5.3 can be used through the GLM Coding Plan, ZCode, Claude Code, OpenCode, and other coding agent workflows. By combining stronger coding performance, long-horizon task execution, post-training scale, cyber evaluation, reasoning effort controls, and coding-agent integrations, GLM-5.3 supports advanced developer and research workflows.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

APIFree No 
C No 
ClinePass No 
Cosmos No 
Factory Droid No 
HTML No 
Hermes Agent No 
Java No 
Kilo Code No 
LM Studio Bionic No 
OpenClaw No 
OpenCode Zen No 
OpenRouter No 
PHP No 
Qoder No 
R No 
Rust No 
Sup AI No 
Swift No 
Z.ai No 

Integrations

APIFree Yes 
C Yes 
ClinePass Yes 
Cosmos Yes 
Factory Droid Yes 
HTML Yes 
Hermes Agent Yes 
Java Yes 
Kilo Code Yes 
LM Studio Bionic Yes 
OpenClaw Yes 
OpenCode Zen Yes 
OpenRouter Yes 
PHP Yes 
Qoder Yes 
R Yes 
Rust Yes 
Sup AI Yes 
Swift Yes 
Z.ai Yes 

Pricing Details

$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 Trial No 
Free Version No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Abliteration.ai

Founded

2025

Country

United States

Website

abliteration.ai/

Vendor Details

Company Name

Z.ai

Founded

2023

Country

China

Website

z.ai/

Product Features

Alternatives

No Alternatives

Alternatives

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