GLM-5 KING MODE: I have LEFT OPUS & CODEX for this FULLY FREE SETUP!

GLM5 & King Mode: A Powerful Coding Setup for 2026

Key Concepts:

• GLM5: A 744 billion parameter mixture of experts open-source model developed by ZAI, designed as a “system architect” model.
• King Mode: A system prompt designed to improve model focus and discipline, eliminating unnecessary verbosity and promoting direct output.
• Ultraink Trigger: A keyword within King Mode that activates deep architectural reasoning within the model.
• Verdant: A platform enabling parallel agent execution with isolated git worktrees for collaborative coding.
• Mixture of Experts (MoE): A neural network architecture where different parts of the model specialize in different tasks, activating only a subset of parameters for each input.
• Rowle Security (RLS): A security mechanism in databases like Superbase that controls access to data based on user roles and permissions.
• Superbase: An open-source alternative to Firebase, offering database, authentication, and real-time capabilities.

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GLM5: The Foundation – A System Architect Model

The video centers around the synergistic combination of GLM5, a recently released open-source model from ZAI, and the King Mode system prompt. GLM5 is described as a 744 billion parameter mixture of experts model, with 40 billion parameters active per pass. ZAI’s stated goal was to create the first open-source system architect model – a model capable of planning, reasoning, and asking clarifying questions. The speaker highlights GLM5’s performance, noting it outperformed OpenAI’s Opus 4.6 on several benchmarks including spelt conban (a spelling correction benchmark), the Nookstack Overflow clone, and the Expo movie tracker. Crucially, GLM5 is currently available for free use through Kilo Code.

The Need for King Mode – Discipline for Brilliance

Despite GLM5’s inherent intelligence, the speaker argues it requires discipline. While capable of extended reasoning (up to 3 hours on tasks like Atari apps), GLM5 sometimes overthinks simpler tasks, hindering performance. The ZAI team themselves acknowledged this tendency. King Mode addresses this by adding structure, prompting the model to assess complexity and choose between deep architectural reasoning and quick execution. The “ultrathink” trigger within King Mode is key to activating this behavior. King Mode also eliminates unnecessary verbose explanations, focusing the model on delivering code directly – a feature enabled by the “zero fluff” directive. The analogy used is that GLM5 is a brilliant architect prone to overthinking, while King Mode acts as a project manager ensuring focus and efficient delivery.

Verdant: Orchestrating Parallel Agents

The speaker emphasizes that the true power of this combination is unlocked by using Verdant. While King Mode improves a model within a standard chatbot, Verdant allows for the execution of multiple GLM5 agents in parallel, each with its own isolated git worktree. This enables simultaneous work on different aspects of a project – for example, one agent handling backend architecture while another focuses on the frontend. Each agent benefits from the full King Mode context, operating independently and producing high-quality code. This effectively transforms a single brilliant architect into an entire team.

Setup and Configuration – A Simple Process

The setup process is described as straightforward:

1. Open Verdant: Launch the Verdant platform.
2. Select GLM5: Choose GLM5 as the model within Verdant’s settings.
3. Inject King Mode Prompt: Paste the full King Mode prompt into Verdant’s project rules or system instructions area. The speaker advises against including the front-end design skill in the prompt for GLM5, as its architectural strengths already cover structured code and layout. Specific aesthetic preferences should be communicated directly in the prompt.
4. Use “Ultrathink”: Prefix complex prompts with the “ultrathink” keyword to activate the deep reasoning capabilities of King Mode.

Real-World Demonstration: A Full-Stack Seas Dashboard

The speaker demonstrates the setup by building a full-stack seas (likely a typo for SaaS) dashboard with authentication, a database layer, and real-time analytics. The workflow involves:

• Agent 1 (Backend): Prompted to set up a Superbase backend, including database schema creation (users, events, sessions tables), row-level security policies, and edge functions for data ingestion. The agent correctly identified the need for Superbase Realtime subscriptions for real-time analytics and implemented multi-tenancy support through organization ID filtering in RLS policies.
• Agent 2 (Frontend): Prompted to initialize a Next.js 14 project with Tailwind, build the dashboard layout (sidebar, metrics bar, chart area), and implement a real-time line chart. The agent considered component structure, error boundaries, and memoization for performance optimization.
• Agent 3 (Integration): Prompted to review the code from Agents 1 and 2, connect the backend and frontend, create a server action for data fetching, and add error handling and loading states. This agent autonomously created a custom hook for the real-time subscription.

The entire process, from initial prompt to integrated dashboard, took approximately 5 minutes of user interaction, with the agents handling the bulk of the coding.

Comparison to GLM4.7 – A More Streamlined Approach

The speaker contrasts this workflow with their previous experience using GLM4.7, which required combining King Mode and a front-end skill to achieve comparable results. GLM4.7 needed assistance with visual design, whereas GLM5’s inherent architectural intelligence eliminates the need for this additional crutch. King Mode alone is sufficient to unlock GLM5’s full potential.

Practical Considerations & Cost

The speaker notes that GLM5 operates with reasoning effort levels, recommending a medium setting for most tasks and high for complex architectural decisions. Combining high reasoning effort with “ultrathink” results in deeper thinking but slower execution. They also advise against using “ultrathink” for simple chat requests, as it’s unnecessary and triggers full architectural reasoning for trivial tasks. While GLM5 is more parameter-heavy than GLM4.7 and therefore potentially more expensive, the speaker anticipates similar pricing to the coding plans offered by ZAI, remaining significantly cheaper than alternatives like Anthropic’s Opus. The open-weight nature of the model is also highlighted as a major benefit.

Conclusion: A Powerful and Accessible Coding Solution

The speaker concludes that the combination of GLM5’s intelligence, King Mode’s discipline, and Verdant’s orchestration creates a remarkably powerful and accessible coding solution. This setup effectively transforms a relatively inexpensive open-source model into a capable development team, significantly boosting productivity. The link to the King Mode prompt is provided in the video description. The core takeaway is that this combination represents a potentially game-changing development workflow for 2026.