GLM 5 Blog
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Read about our latest product features, solutions, and updates.
GLM 5.2 API: Endpoints, Authentication, and Python Integration Guide
GLM 5.2 uses the OpenAI SDK format with a different base_url and model name. Here is the complete guide to endpoints, authentication, streaming, and Python integration.
GLM 5.2 Context Window: What 1 Million Tokens Actually Means
GLM 5.2 supports 1,048,576 tokens — 8x GPT-4o's 128K. Here is what that capacity enables for codebases, documents, and long agent sessions, and when it matters.
GLM 5.2 for Coding: Benchmarks, Best Prompts, and IDE Integration
GLM 5.2 scores 62.1% on SWE-bench Pro and 78% on Terminal-Bench. Here is how to use it as a coding assistant, what prompt patterns work best, and how to integrate it with VS Code and Cursor.
GLM 5.2 for Data Analysis: Structured Output, SQL Generation, and Python Workflows
GLM 5.2's 1M context window and JSON mode make it practical for large-scale data analysis. Here is how to use it for SQL generation, CSV analysis, structured extraction, and Python data workflows.
GLM 5.2 GGUF: Quantized Weights and Local Inference Guide
GLM 5.2's MIT-licensed weights can be quantized to GGUF format for local inference. Here is the hardware requirements at each quantization level, and how to set up inference with llama.cpp and LM Studio.
GLM 5.2 JSON Mode: Structured Output and Schema Enforcement
GLM 5.2 supports JSON mode via response_format — the model outputs valid, parseable JSON every time. Here is how to use it for structured extraction, data pipelines, and schema-enforced AI responses.
GLM 5.2 License: MIT Open Weights and What It Means for Commercial Use
GLM 5.2 weights are MIT-licensed with no commercial restrictions. Here is what you can do — fine-tune, redistribute, build products — and how MIT compares to Llama and Apache licenses.
GLM 5.2 on OpenRouter: Access, Pricing, and Integration Guide
GLM 5.2 is available on OpenRouter as z-ai/glm-5.2. Here is how to access it, how OpenRouter pricing compares to Z.ai direct, and how to switch from any other model with one line of code.
GLM 5.2 Pricing: API Cost, Plans & Free Tiers
GLM 5.2 pricing, decoded: $1.40/$4.40 per 1M tokens on Z.ai, cheaper via OpenRouter, plus Coding Plan subscriptions and free ways to run it. Full breakdown.
GLM 5.2 API Rate Limits: Tiers, Quotas, and Error Handling
GLM 5.2 API rate limits vary by Z.ai subscription tier. Here is the tier structure, how to handle 429 errors with exponential backoff, and strategies for scaling high-volume production workloads.
GLM 5.2 System Prompt Guide: Templates for Coding, Analysis, and Writing
The system prompt sets the frame for everything GLM 5.2 outputs. Here are proven templates for code generation, document analysis, and structured extraction, with token-efficiency tips.
GLM 5.2 Temperature and Sampling: How to Control Output Quality
GLM 5.2's temperature, top-p, and top-k parameters control randomness and creativity. Here are the recommended settings for coding, analysis, creative writing, and structured extraction — with concrete examples.
GLM 5.2 Thinking Mode: How Extended Reasoning Works
GLM 5.2 supports an extended thinking mode that exposes the model's reasoning chain before the final answer. Here is how thinking mode works, when to enable it, and how it affects cost and response quality.
Grok 4.6 API: Pricing, Context Window, and How to Use It
A practical guide to Grok 4.6 pricing, its 500K-token context window, reasoning controls, and how to choose the right prompt size.
Run GLM 5.2 Locally: Ollama, VRAM & Hardware Guide
Honest GLM 5.2 local guide: Ollama's cloud tag isn't local inference. Here's the VRAM you need by quant tier and exact llama.cpp steps for Mac and Linux.
What Is GLM 5.2? Features, Specs & Open Weights
What is GLM 5.2? Z.AI's open-weight LLM with a 1M-token context window for coding and agents. Here's what it does, how it compares, and how to try it free.