#ChatGLM
39 related articles
·4 min
ChatGLM Large Model Development Tutorial: From Zero to Enterprise Deployment
Systematically learn ChatGLM large model development, covering Transformer principles, RAG, private deployment, fine-tuning, and Agent development, with a roadmap and hands-on cases.
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·3 min
The GLM5.5 Leak Controversy: How the AI Community Distinguishes Real Leaks from Fake Ones
Reddit circulated a leaked GLM5.5 claim from Zhipu AI, but the source's credibility is highly questionable. Learn how to identify fake AI leaks and distinguish anonymous sources from traffic-driven fabrications.
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·3 min
Qwen Next-Gen, DeepSeek V4, New GLM Spotted Simultaneously: China's LLM Race Accelerates
Qwen next-gen (KLab), DeepSeek V4 GA, and Zhipu GLM's new version are all in testing simultaneously. A deep dive into the latest developments and tech trends.
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·3 min
Qwen3 Deep Dive: A Complete Look at the Open-Source Hybrid Reasoning Model
Qwen3 deep dive: 6 Dense & MoE models from 0.6B to 235B, world's first open-source hybrid reasoning model, matching Gemini 2.5 Pro. Complete guide for developers and enterprises.
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·4 min
Understanding Transformer From the Ground Up: How Language Models Predict the Next Word
From Tokenization and Embedding to the Attention mechanism, this article systematically breaks down how Transformer works — and how ChatGPT turns input text into next-token probabilities.
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·2 min
GLM Open-Source Model: Can a Million-Token Context Window Challenge Claude Code?
GLM open-source LLM claims 1M-token context, local deployment, and coding ability rivaling Claude Code. We break down the three key selling points and evaluate the hype vs. reality.
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·3 min
The Real Risks of Third-Party ChatGPT Top-Up Services: Don't Let a Bargain Cost You Your Account
Are third-party ChatGPT top-up services really safe? This deep dive unpacks how they work, the ban risks, and financial dangers — plus the right way to subscribe officially.
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·3 min
AI Large Language Models for Beginners: Core Concepts and Chinese Model Landscape
New to AI? This guide clarifies AI, machine learning, deep learning, and LLMs, traces milestones from Deep Blue to DeepSeek, and maps out China's LLM landscape.
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·3 min
GPUStack in Action: Complete Guide to Day 0 Deployment of DeepSeek-V4-Flash
Deploy DeepSeek-V4-Flash DSpark on 8× H20-141G using GPUStack's SGLang backend on Day 0. Full walkthrough of Web UI config, parameter tuning, and 200 tokens/sec benchmark results.
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·4 min
AI Large Language Models for Beginners: Core Concepts, History, and China's Model Landscape
A beginner's guide to AI large models: clarify the relationships between AI, ML, deep learning, and LLMs, trace the journey from Deep Blue to ChatGPT and DeepSeek, and explore China's model landscape.
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·4 min
Claude Sonnet 5 In-Depth Review: Impressive Performance, but Hidden Traps in the Pricing Strategy
A full review of Claude Sonnet 5: major agentic gains, benchmarks near Opus 4.8, but a Tokenizer switch inflates real costs, nearly erasing the price gap with Opus. We break down the pricing traps.
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·2 min
GLM-5.2 Spotted in Testing | Claude Fable 5 Launches: 4 Key AI Updates
GLM-5.2 spotted in testing, Anthropic launches Claude Fable 5, Moore Threads open-sources MusaCoder for domestic GPUs, and Google releases Gemini real-time translation.
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·7 min
Getting Started with OpenAI LLM Development: A Practical Guide to Model Selection, Token Pricing, and API Usage
A systematic guide to the three cores of OpenAI LLM app development: GPT-4/GPT-3.5 model selection, token billing and cost-saving tips, and practical use of the Models, Completion, and Chat Completion APIs.
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·7 min
A Java Developer's Guide to AI: Framework Selection and Practical Tutorial for LangChain4J
As LLM costs keep falling, how can Java developers seize the AI opportunity? This article explores LangChain4J's core capabilities, supported models and vector databases, and compares LangChain4J vs. Spring AI to help you build local knowledge bases and intelligent customer service systems.
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·6 min
The Complete Guide to GLM-5.2: Hands-On Review of an Open-Source Long-Context Model
An in-depth hands-on review of Zhipu AI's flagship GLM-5.2: 1M-token context, strong coding, mature agent workflows—at one-fifth the price of top frontier models. Covers website testing, Cursor integration, MCP tooling, and production migration.
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·3 min
GLM 5.2 Deep Dive: The Open-Source Coding Model Breaking Into the Global Top Three
GLM 5.2 by Zhipu AI: fully open-source under MIT license, #3 globally on Code V3 with a 96-point S-tier rating, and a genuinely usable 1M-token context window.
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·3 min
GLM 5.2 In-Depth Review: How an Open-Source Model Truly Stacks Up Against Closed-Source Giants
In-depth review of Zhipu AI's open-source flagship GLM 5.2: benchmarks, frontend dev, 3D game generation, and cost analysis. MIT licensed, top-5 scores, Opus-level frontend quality at 1/8 the cost.
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Tech Frontiers·2 min
GLM-5.2 Tops Global Open-Weight Model Rankings: Leading the Industry in Frontend Coding
Zhipu AI's GLM-5.2 tops the Artificial Analysis Intelligence Index for open-weight models and is recognized as the world's top frontend coding model. A deep dive into its performance and the shifting open-source AI landscape.
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·2 min
GLM5.2 Frontend Development Capabilities Tested: Better Aesthetics Than GPT5.5?
Hands-on comparison of GLM5.2 vs GPT5.5 frontend development: GLM5.2 edges ahead in page aesthetics but slow inference and limited API access remain major drawbacks.
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·2 min
A Guide to Free Access to Mainstream AI Models in China: Options and Pitfalls
A guide to free access to mainstream AI models like GPT, Gemini, DeepSeek, and Kimi in China, covering aggregator site risks and recommended legitimate alternatives.
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