GLM-4.7-Flash Model

Description

GLM-4.7-Flash is a cutting-edge 30B-A3B MoE model that offers a new option for lightweight deployment, balancing performance and efficiency. It is recognized as the strongest model in the 30B class, providing significant advantages for AI applications. The model has demonstrated impressive results across various benchmarks, including AIME 25, GPQA, LCB v6, HLE, SWE-bench Verified, τ2-Bench, and BrowseComp. These benchmarks highlight its superior performance compared to other models like Qwen3-30B-A3B-Thinking-2507 and GPT-OSS-20B.

GLM-4.7-Flash supports local deployment through inference frameworks such as vLLM and SGLang, with comprehensive deployment instructions available in the official GitHub repository. The model is optimized for various tasks with default settings, including temperature, top-p, and max new tokens. For multi-turn agentic tasks, Preserved Thinking mode is recommended to enhance performance.

The model's versatility is further demonstrated by its ability to handle different domains, such as Retail and Telecom, with specific prompts to avoid failure modes. The model's adaptability makes it suitable for a wide range of applications, from research to practical AI deployments. With over 1.8 million downloads last month, GLM-4.7-Flash is a popular choice among AI practitioners.

Overall, GLM-4.7-Flash offers a robust solution for those seeking a high-performance AI model that is both efficient and easy to deploy. Its strong benchmark results and support for local deployment make it an attractive option for various industries and use cases.

GLM-4.7-Flash Model Highlights

• 30B-A3B MoE model

• Lightweight deployment

• High performance on benchmarks

• Supports vLLM and SGLang

• Preserved Thinking mode

• Domain-specific prompts

• 1.8M+ downloads last month

• Comprehensive deployment instructions

Getting Started with GLM-4.7-Flash Model

1. 1

   Access page: Visit the Hugging Face model page

2. 2

   Load model: Download GLM-4.7-Flash

3. 3

   Configure environment: Set up vLLM or SGLang

4. 4

   Integrate: Use API services on Z.ai API Platform

GLM-4.7-Flash Model's Use Cases

• AI Research
• Retail Applications
• Telecom Solutions
• Benchmark Testing
• Local Deployment

FAQ from GLM-4.7-Flash Model

• What is GLM-4.7-Flash?

  GLM-4.7-Flash is a 30B-A3B MoE model designed for lightweight deployment, balancing performance and efficiency.

• How does GLM-4.7-Flash perform on benchmarks?

  It excels in various benchmarks, outperforming models like Qwen3-30B-A3B-Thinking-2507 and GPT-OSS-20B.

• Can GLM-4.7-Flash be deployed locally?

  Yes, it supports local deployment through vLLM and SGLang frameworks.

• What are the default settings for GLM-4.7-Flash?

  Default settings include temperature: 1.0, top-p: 0.95, and max new tokens: 131072.

• Is there support for multi-turn tasks?

  Yes, Preserved Thinking mode is recommended for multi-turn agentic tasks.

• How popular is GLM-4.7-Flash?

  It had over 1.8 million downloads last month.

• What domains can GLM-4.7-Flash handle?

  It can handle domains like Retail and Telecom with specific prompts.

• Where can I find deployment instructions?

  Comprehensive deployment instructions are available in the official GitHub repository.