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What is Microsoft-Decision-1?

Microsoft-Decision-1 is a highly effective decision-scoring model specifically designed for structured outputs, allowing software systems to take swift actions. This innovative model supports a range of functionalities including routing, classification, prioritization, verification, and workflow management, applicable across various applications, agents, and automated systems. Developed through post-training of Qwen3.5-9B, it excels in single-pass decision scoring and delivers calibrated probabilities for a defined set of response choices. The model is adept at addressing yes/no inquiries, multiple-choice situations, rating scales, and rubric-based assessments of AI-generated outputs and agent performances via a structured API. Comprehensive evaluations carried out by Microsoft across 36 benchmarks covering routing, ranking, long-context understanding, multilingual functions, and tasks outside conventional distributions demonstrate that it achieved top accuracy levels with impressively low latency. Additionally, the model places a strong emphasis on robustness, with extensive testing conducted to ensure decision-making stability even when prompts undergo rephrasing or modifications. This commitment to stability highlights its potential for delivering reliable performance in diverse real-world scenarios, making it a versatile tool for various industries.

What is GLM-5.3?

GLM-5.3 is Z.ai’s frontier coding model built to improve complex software engineering, long-horizon agent work, and advanced technical reasoning through scaled post-training. The model uses the same base model as GLM-5.2, with performance gains coming from additional post-training environments, more diverse tasks, and expanded compute on the existing training stack. Z.ai’s stack includes IndexShare for efficient long-context processing, SAO for reinforcement learning on long-horizon tasks, and slime for large-scale asynchronous post-training. GLM-5.3 is designed to perform better on work that resembles real engineering tasks rather than short coding exercises. Its training environments include production-style workflows where the model must diagnose bottlenecks, inspect documentation, use codebases, run experiments, implement changes, and produce measurable improvements. The model improves coding performance across public and private benchmarks, including Terminal Bench 3.0, DeepSWE, Agents’ Last Exam, and Z.ai Code Bench. GLM-5.3 also improves token efficiency, producing stronger agentic coding results than GLM-5.2 while using fewer output tokens in Z.ai’s internal evaluations. The model supports three reasoning effort levels, low, high, and max, and no longer supports disabling thinking. Z.ai recommends max reasoning effort for coding tasks, while applications using disabled thinking must migrate to enabled thinking before switching to GLM-5.3. The release also reports emergent cyber capabilities, including stronger vulnerability discovery and exploitation-chain reasoning, with open-weight release planned after safety evaluation and hardening. By combining scaled post-training, long-context infrastructure, long-horizon reinforcement learning, coding-agent workflows, benchmark improvements, reasoning controls, and ZCode integration, GLM-5.3 helps developers and researchers work on demanding coding and agentic tasks.

Media

Media

Integrations Supported

OpenRouter
Microsoft Foundry

Integrations Supported

OpenRouter
C#
Cherry Studio
ClinePass
Factory Droid
Java
JetBrains Junie
Kotlin
LM Studio
OpenCode Go
OpenCode Zen
Python
Roo Code
Swift
Tabbit Browser
Vercel AI Gateway
Wafer
Yonoo
scikit-learn

API Availability

Has API

API Availability

Has API

Pricing Information

$0.042 per 1M tokens

Pricing Information

Free
Open source
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

commandline.microsoft.com/microsoft-decision-1-model-foundry/

Company Facts

Organization Name

Z.ai

Date Founded

2023

Company Location

China

Company Website

z.ai/

Categories and Features

AI Decision Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

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