Altar-1Aikido Security
|
Qwen2Alibaba
|
|||||
Related Products
|
||||||
About
Aikido Altar is an open-weight security model built to bring frontier-grade defensive security intelligence into infrastructure organizations' control. It is designed for sovereign security environments where sensitive source code, architecture documentation, vulnerability findings, and other internal context cannot be sent to third-party inference services. Altar is based on GLM-5.3 and uses quantization and expert pruning to reduce the model from 1.51 TB at full precision to 328 GB while preserving most of the parent model’s reasoning and security capabilities. It retains 168 of the original 256 routed experts per backbone expert layer and uses a W4A16 representation, making deployment more practical for agentic security workloads with large and growing context windows. Expert selection was calibrated using internal pentesting traces and multilingual data, with no customer data involved, to preserve cybersecurity, coding, and language understanding.
|
About
Qwen2 is the large language model series developed by Qwen team, Alibaba Cloud.
Qwen2 is a series of large language models developed by the Qwen team at Alibaba Cloud. It includes both base language models and instruction-tuned models, ranging from 0.5 billion to 72 billion parameters, and features both dense models and a Mixture-of-Experts model. The Qwen2 series is designed to surpass most previous open-weight models, including its predecessor Qwen1.5, and to compete with proprietary models across a broad spectrum of benchmarks in language understanding, generation, multilingual capabilities, coding, mathematics, and reasoning.
|
|||||
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
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
|
|||||
Audience
Security teams and regulated organizations needing to run AI-powered vulnerability research, code analysis, remediation, and pentesting entirely within infrastructure they control
|
Audience
AI developers interested in a powerful LLM
|
|||||
Support
Phone Support
Not Supported
24/7 Live Support
Supported
Online
Supported
|
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
|
|||||
API
Offers API
Supported
|
API
Offers API
Not Supported
|
|||||
Screenshots and Videos |
Screenshots and VideosNo images available
|
|||||
Pricing
$350 per month
Free Version
Supported
Free Trial
Not Supported
|
Pricing
Free
Open source
Free Version
Supported
Free Trial
Not Supported
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
|
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
|
|||||
Company InformationAikido Security
Founded: 2022
Belgium
www.aikido.dev/blog/aikido-altar-open-weight-ai-sovereign-security
|
Company InformationAlibaba
Founded: 1999
China
github.com/QwenLM/Qwen2
|
|||||
AlternativesNo Alternatives
|
Alternatives |
|||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
Categories |
Categories |
|||||
Integrations
C
Not Supported
CSS
Not Supported
Clojure
Not Supported
Elixir
Not Supported
Go
Not Supported
HTML
Not Supported
Horay.ai
Not Supported
Hugging Face
Not Supported
Java
Not Supported
JavaScript
Not Supported
|
Integrations
C
Supported
CSS
Supported
Clojure
Supported
Elixir
Supported
Go
Supported
HTML
Supported
Horay.ai
Supported
Hugging Face
Supported
Java
Supported
JavaScript
Supported
|
|||||
|
|
|