Average Ratings 0 Ratings
Average Ratings 1 Rating
Description
GLM-Legal is an AI language model developed by Z.ai to support legal analysis, document review, compliance research, and autonomous legal workflows. The model is built on GLM-5.3-Flash and incorporates specialized legal training to improve performance on professional legal tasks. Its contract analysis capabilities help users examine agreements, identify problematic provisions, and recommend revisions based on specific client objectives. GLM-Legal can analyze collections of legal documents, identify contradictions between evidence sources, and connect factual findings to relevant legal arguments. The model also supports regulatory compliance research, including analysis of privacy laws, cross-border requirements, and jurisdiction-specific obligations. Its agentic architecture enables multistep legal workflows involving document ingestion, legal reasoning, source referencing, and structured deliverable generation. Integration with Z.ai's AutoClaw platform is intended to support document editing, tracked changes, comments, and other practical legal work processes. Z.ai reports that GLM-Legal achieved a 19.2% all-pass rate on Harvey's Legal Agent Benchmark and demonstrated competitive performance on LegalBench and PLawBench. The model is intended for law firms, corporate legal departments, legal technology providers, and independent practitioners seeking AI assistance with complex legal work.
Description
Gemini 4 Argon is a frontier AI model from Google DeepMind built to sustain deep reasoning across complex, long-running professional workflows. Google designed the model for demanding work spanning software engineering, finance, legal tasks, enterprise knowledge work, cybersecurity defense, and creative writing. Argon supports coding, reasoning, multimodality, and multi-step task execution, allowing it to work across workflows that require information gathering, analysis, tool use, and extended problem solving. Its output token limit has been increased from 64,000 to 1 million tokens, giving the model additional capacity for lengthy reasoning and generation within a single trajectory. On DeepSWE v1.1, Google reports a score of 77.9% for real-world long-horizon software engineering, while its AutomationBench score of 51.3% measures performance on end-to-end business workflows. Google also reports strong results on evaluations covering finance, legal work, visual analysis, and long-video understanding, including a 91.7% score on LVBench. For cybersecurity teams, Argon can autonomously discover, validate, and patch software vulnerabilities and achieved a reported 68% score on CWE-bench v1. Google is initially providing the model to selected cyber defenders through its Fairwind Program while strengthening safeguards before expanding access to developers, enterprises, and consumers. Argon is planned to launch at an introductory price of $2 per million input tokens and $10 per million output tokens, with cached input tokens receiving a 95% discount from the standard input price.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Agent Search on Gemini Enterprise Agent Platform
No
C
No
C++
No
Dart
No
Devin Desktop
No
Gemini 3.8 Flash Cyber
No
Gemini Enterprise Agent Platform Notebooks
No
Google AI Mode
No
Google AI Studio
No
HTML
No
Integrations
Agent Search on Gemini Enterprise Agent Platform
Yes
C
Yes
C++
Yes
Dart
Yes
Devin Desktop
Yes
Gemini 3.8 Flash Cyber
Yes
Gemini Enterprise Agent Platform Notebooks
Yes
Google AI Mode
Yes
Google AI Studio
Yes
HTML
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$2 per 1M tokens (input)
$2 per million input tokens and $10 per million output tokens, with cached input tokens priced at 95% off input token price.
Free Trial
No
Free Version
No
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
No
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
No
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
Z.ai
Founded
2019
Country
China
Website
z.ai/blog/glm-legal
Vendor Details
Company Name
Founded
1998
Country
United States
Website
gemini.com