Chinese Open-Source DOMINATES Coding (GLM-4.5)

Introduction and Demos 00:00

  • China is leading the advancement of open-source AI models, with the new GLM 4.5 model from ZAI matching top closed-source models in reasoning, coding, and agent capabilities.
  • Demo of the model simulating a Rubik’s cube—successfully scrambles and solves cubes of increasing difficulty (3x3, 5x5, 10x10).
  • The model outputs move history and allows custom features, such as setting the number of scrambles.
  • Demonstrates solving the Tower of Hanoi puzzle, performing deep reasoning without relying on pre-written code, and provides visualized solutions.
  • The model builds interactive 3JS Lego simulations in a single HTML file, and can build upon previous structures with reasonable accuracy.
  • Creates a 3D solar system visualization with adjustable settings, tooltips for planetary data, and interactive features like scaling, lighting, and orbit visibility.

Model Details and Benchmarks 06:00

  • GLM 4.5 comes in two versions: the standard (355B total, 32B active parameters) and the "air" version (106B total, 12B active parameters), both using a mixture-of-experts architecture.
  • These are hybrid reasoning models with “thinking” and “non-thinking” modes for various tasks.
  • In practical use, GLM 4.5 tends to engage in its thinking mode even with simple prompts.
  • Benchmark performance places GLM 4.5 very close to leading closed-source models (e.g., Grok 4), outperforming models like Claude 4 Opus.
  • The smaller “air” version also ranks competitively.
  • On agentic and tool-use benchmarks, GLM 4.5 exceeds Grok 4 and aligns with other frontier models.
  • For reasoning benchmarks (MMLU, Math 500), it is above Claude 4 Opus but still trails some models like Deepseek R1 and Gemini 2.5 Pro.
  • On coding benchmarks, GLM 4.5 ranks near the top—just below Claude.
  • In terms of parameter efficiency on SWE-bench, GLM 4.5 matches Kimmy K2 in quality but is significantly smaller in size.
  • The model uses reinforcement learning for post-training agentic capabilities, in line with current state-of-the-art methods.

Additional Demos and Recap 09:30

  • Demonstrates more model capabilities: Flappy Bird game simulation, accurate 3D Maze Explorer, to-do board interface, animated visualizations (SVG), Python-generated visualizations, and a Pokedex with interactive stats and images.
  • Revisits the Tower of Hanoi demo with 10 disks; the model provides an algorithmic solution and accurately solves the problem in 1,023 moves, displaying each step at 10 moves per second.
  • Open-source models like GLM 4.5 have effectively closed the gap with top closed-source AI, at least until the release of GPT-5.
  • The video ends with a call to support the channel.