GLM 4.7: New SOTA Coding KING? Powerful, Fast, & Cheap! Really Good AT Coding! (Fully Tested)

GLM 4.7: A Detailed Overview & Performance Analysis

Key Concepts: GLM 4.7, Open-Source LLM, Coding Benchmarks (Agentic, Multilingual, Terminal), Tool Use, Interleaved Thinking, Preserved Thinking, Turnle Thinking, Context Length (202k tokens), API Access (Hilo Code, Open Router, Alamarina), Front-End Generation, Proprietary Model Comparison (Gemini 3.0, Claude Sonnet 4.5, GPT-5.1).

I. Introduction & Core Capabilities of GLM 4.7

GLM 4.7, developed by ZAI, represents a significant advancement in open-source Large Language Models (LLMs). It builds upon GLM 4.6 and demonstrates substantial improvements across several key areas: code quality, complex reasoning, and tool usage. The model excels in chat, creative writing, and role-playing scenarios. Notably, GLM 4.7 achieved a score of 73.8% on the Swaybench verified benchmark – a remarkable result for an open-source model – and 41% on Terminal Bench. Crucially, it surpasses models like Claude Sonnet 4.5 and GPT-5.1 in tool use benchmarks. It also demonstrates strong performance in math (GPQA), browser compatibility, and consistently outperforms GLM 4.6 while remaining competitive with top proprietary models like Gemini 3.0 and Claude Sonnet 4.5. Testing encompassed 17 benchmarks covering reasoning, coding, and agent tasks.

II. Performance Benchmarks & Comparative Analysis

The model shows the most substantial gains over GLM 4.6 in Human Level Evaluation (HLE) and tool usage. Its front-end code quality and performance on the Gent task are significantly improved. A key advantage is its ability to utilize tools more effectively than Cloud Sonic 4.5.

• Cost Efficiency: GLM 4.7 is reported to be four to seven times cheaper than most proprietary models, making it an attractive option.
• Front-End Generation: A direct comparison of landing page generation between GLM 4.7 and 4.6 reveals a dramatic improvement in quality with the newer version.
• Gemini 3 Pro vs. GLM 4.7 (Spotify Clone): Initial attempts to generate a Spotify clone with GLM 4.7 yielded poor results, failing to accurately replicate the interface. However, utilizing Kilo Code improved the output, though it still didn’t match the quality of Gemini 3 Pro’s generation.
• Browser-Based Operating System: GLM 4.7 successfully generated a functional browser-based operating system for 60 cents, replicating elements of macOS (Safari, Notes, Calculator, Terminal, Calendar, System Settings, Dark Mode, Wallpaper customization).
• SVG Generation (Butterfly): The model produced a decent animated butterfly SVG with a background, symmetrical design, and functional animation, though not the best possible generation.
• Minecraft Clone: GLM 4.7 generated a remarkably functional Minecraft clone ("Webcraft") with block placement, breaking, jumping, texturing, and core gameplay mechanics, considered the best single-shot generation of a Minecraft clone seen to date.
• AI Research Paper Identification: GLM 4.7 successfully identified the top five most cited AI research papers from the past 12 months using the Semantic Scholar API, demonstrating effective tool calling and information retrieval. The identified key trends included medical AI dominance, foundational models, autonomous agents, evaluation methodology, and computer vision.
• Karum Board Game: GLM 4.7 generated a functional Karum board game, allowing gameplay, while Gemini 3 Pro’s attempt failed to function.

III. Novel Reasoning Modes: Interleaved, Preserved, and Turnle Thinking

GLM 4.7 introduces three new reasoning modes:

• Interleaved Thinking: Enables the model to "think before actions," improving accuracy and efficiency.
• Preserved Thinking: Allows the model to retain reasoning across multi-turn tasks, maintaining context and coherence.
• Turnle Thinking: Provides control over reasoning per request, optimizing for accuracy, stability, and cost-effectiveness, particularly in complex, long-running workflows.

IV. Technical Specifications & Access Methods

• Knowledge Cutoff: Mid to late 2024.
• Context Length: 202k tokens.
• Pricing: $0.44 per 1 million input tokens, $1.74 per 1 million output tokens.
• Access Points:
  • ZI’s Chatbot: Direct access with the option to utilize "deep thinking."
  • Hugging Face Model Card: Available for download and integration.
  • Hilo Code: Free API access for GLM 4.7.
  • Open Router: Paid API access.
  • Alamarina: Free access via battle arena or direct chat.
  • Kilo Code (IDE Extension): Free access via API integration within an IDE.

V. Demonstration: Landing Page Generation with Kilo Code

The video demonstrates generating a sports store landing page using Kilo Code and GLM 4.7. The process involved the model autonomously planning the structure, designing the layout, and implementing components like a bold headline and animated tickers. The generation took approximately 5 cents and showcased the model’s ability to leverage tools and generate code autonomously. While requiring minor adjustments (placeholder text, font settings), the generated structure provided a strong foundation for further editing.

VI. Notable Quote

“This is one of the best models that I have ever seen in terms of its front end.” – Demonstrating the high quality of the generated outputs.

VII. Conclusion

GLM 4.7 represents a significant leap forward in open-source LLMs, offering competitive performance against proprietary models at a fraction of the cost. Its advancements in reasoning, tool usage, and front-end generation, coupled with its large context window and accessible API options, position it as a powerful and versatile tool for developers and researchers. The introduction of interleaved, preserved, and turnle thinking modes further enhances its capabilities for complex tasks and long-running workflows. The model’s performance, particularly in coding and creative tasks, is highly promising, making it a noteworthy contender in the rapidly evolving AI landscape.