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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.

Description

MAI-Cyber-1-Flash represents Microsoft AI's streamlined, code-intensive security framework designed to detect vulnerabilities within intricate code structures. Originating from the MAI-Thinking-1 family and constructed from the ground up utilizing superior data, it is seamlessly embedded within MDASH, Microsoft's comprehensive system for identifying and addressing vulnerabilities through multiple agents. MDASH leverages over 100 expertly fine-tuned agents along with several advanced models to efficiently locate, confirm, and resolve software vulnerabilities, while MAI-Cyber-1-Flash capably manages up to 90% of related tasks. For particularly complex scenarios, larger models like GPT-5.4 can be engaged, ensuring an expertly calibrated multi-model approach that optimally assigns the appropriate model for each specific task. This collaboration between MDASH and MAI-Cyber-1-Flash has resulted in an impressive performance of 96% on CyberGym, surpassing competitors like Mythos, Gemini, and GPT-based solutions in their ability to analyze extensive codebases for vulnerability detection. Such advancements signify a major leap in ensuring the security and integrity of software systems in an increasingly complex digital landscape.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Augment Code Yes 
C Yes 
C# Yes 
CSS Yes 
Cherry Studio Yes 
Cursor Yes 
Factory Droid Yes 
GLM Coding Plan Yes 
Go Yes 
HTML Yes 
JetBrains Junie Yes 
LM Studio Yes 
LM Studio Bionic Yes 
PyTorch Yes 
Python Yes 
Qoder Yes 
SQL Yes 
Shiori Yes 
Together AI Yes 
TypeScript Yes 

Integrations

Augment Code No 
C No 
C# No 
CSS No 
Cherry Studio No 
Cursor No 
Factory Droid No 
GLM Coding Plan No 
Go No 
HTML No 
JetBrains Junie No 
LM Studio No 
LM Studio Bionic No 
PyTorch No 
Python No 
Qoder No 
SQL No 
Shiori No 
Together AI No 
TypeScript No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

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 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

Z.ai

Founded

2023

Country

China

Website

z.ai/

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

microsoft.ai/news/introducing-mai-cyber-1-flash-inside-mdash/

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