ShipAny Blog

Blog

Read about our latest product features, solutions, and updates.

GLM 5.2 API: Endpoints, Authentication, and Python Integration Guide

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.

Jul 20, 2026
gglm5.app Team
GLM 5.2 Context Window: What 1 Million Tokens Actually Means

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.

Jul 20, 2026
gglm5.app Team
GLM 5.2 for Coding: Benchmarks, Best Prompts, and IDE Integration

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.

Jul 20, 2026
gglm5.app Team
GLM 5.2 for Data Analysis: Structured Output, SQL Generation, and Python Workflows

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.

Jul 20, 2026
gglm5.app Team
GLM 5.2 GGUF: Quantized Weights and Local Inference Guide

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.

Jul 21, 2026
gglm5.app Team
GLM 5.2 JSON Mode: Structured Output and Schema Enforcement

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.

Jul 21, 2026
gglm5.app Team
GLM 5.2 License: MIT Open Weights and What It Means for Commercial Use

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.

Jul 20, 2026
gglm5.app Team
GLM 5.2 on OpenRouter: Access, Pricing, and Integration Guide

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.

Jul 20, 2026
gglm5.app Team
GLM 5.2 Pricing: API Cost, Plans & Free Tiers

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.

Jun 26, 2026
gglm5.app Team
GLM 5.2 API Rate Limits: Tiers, Quotas, and Error Handling

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.

Jul 21, 2026
gglm5.app Team
GLM 5.2 System Prompt Guide: Templates for Coding, Analysis, and Writing

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.

Jul 20, 2026
gglm5.app Team
GLM 5.2 Temperature and Sampling: How to Control Output Quality

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.

Jul 21, 2026
gglm5.app Team
GLM 5.2 Thinking Mode: How Extended Reasoning Works

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.

Jul 21, 2026
gglm5.app Team
Run GLM 5.2 Locally: Ollama, VRAM & Hardware Guide

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.

Jun 28, 2026
gglm5.app Team
What Is GLM 5.2? Features, Specs & Open Weights

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.

Jun 22, 2026
gglm5.app Team
guide | GLM 5 Blog — Guides, Tutorials, Benchmarks & AI News