Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

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

This repository showcases the research preview of LongLLaMA, an advanced large language model that can manage extensive contexts of up to 256,000 tokens or potentially more. LongLLaMA is developed on the OpenLLaMA framework and has been fine-tuned utilizing the Focused Transformer (FoT) technique. The underlying code for LongLLaMA is derived from Code Llama. We are releasing a smaller 3B base variant of the LongLLaMA model, which is not instruction-tuned, under an open license (Apache 2.0), along with inference code that accommodates longer contexts available on Hugging Face. This model's weights can seamlessly replace LLaMA in existing systems designed for shorter contexts, specifically those handling up to 2048 tokens. Furthermore, we include evaluation results along with comparisons to the original OpenLLaMA models, thereby providing a comprehensive overview of LongLLaMA's capabilities in the realm of long-context processing.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Abliteration.ai Yes 
Venice.ai Yes 

Integrations

Abliteration.ai No 
Venice.ai No 

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
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 No 
Mac No 
Linux No 
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

LongLLaMA

Website

github.com/CStanKonrad/long_llama

Product Features

Alternatives

No Alternatives

Alternatives

Llama 2 Reviews

Llama 2

Meta