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ScrapeGraphAI vs GLM (Z.ai)

ScrapeGraphAIGLM (Z.ai)

Bottom line: ScrapeGraphAI for developers; GLM (Z.ai) for developers building coding agents.

ScrapeGraphAIScrapeGraphAI

Natural-language web scraping that extracts structured data with LLMs

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GLM (Z.ai)GLM (Z.ai)

Open-weight frontier LLM family from Z.ai (Zhipu AI), tuned for coding and agents.

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Votes00
PricingFreemiumFreemium
CategoryWeb ScrapingChatbots
Tags
web-scrapingllmdata-extractionopen-sourceapi
llmopen-sourcecodingagentic
Best for
  • developers
  • data engineers
  • AI pipeline builders
  • Developers building coding agents
  • Teams wanting an open-source frontier model
  • Cost-sensitive API users
Pros
  • Natural-language extraction, no selectors
  • Open-source library with 20,000+ stars
  • Cloud API for teams avoiding infrastructure
  • Resilient to page structure changes
  • Supports multiple LLM backends
  • Open weights under permissive MIT license for major releases
  • Strong performance on open-weight coding and agentic benchmarks
  • Free chat access at chat.z.ai
  • Competitive, low API token pricing
  • Self-hosting and commercial use allowed
Cons
  • LLM extraction can be less precise than hand-coded scrapers
  • Credit-based costs add up at scale
  • Requires volume estimation to control spend
  • Extraction and prompted search cost more credits
  • Best suited to developers
  • Newest releases may hit coding plans before open weights or API pricing
  • Self-hosting the largest MoE models needs significant hardware
  • Coding Plan works only inside officially supported tools
  • Enterprise features like built-in team collaboration are limited
  • China-based provider may raise data-governance questions for some buyers

Comparison generated from each tool's listing. Add or remove tools above to change it.