Lmql vs Spider Cloud

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-09-01
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At a glance

DimensionLmqlSpider Cloud
PricingFree (open-source)Freemium (pay per usage; ~$0.03/1k pages; AI Studio add-on $6/mo)
Primary FocusConstrained LLM generation & prompt programmingWeb crawling & scraping for AI agents
Output TypesStructured data via typed variables, regex, intMarkdown, HTML, JSON, CSV, XML, plain text, screenshots
Key FeatureConstrained decoding (token-level masks, regex, len)Browser AI commands via WebSocket (Act, Extract, Observe)
IntegrationLangChain, LlamaIndex, OpenAI, Transformers, llama.cppLangChain, LlamaIndex, CrewAI, data connectors (S3, GCS, Sheets)
Best ForStructured LLM pipelines & constrained generationReal-time web data for RAG / AI agents

Spider Cloud and LMQL solve different problems: Spider Cloud is a web scraping API optimized for feeding live web data into AI pipelines (with latest Browser AI commands), while LMQL is a programming language for controlling LLM output structure. If you need reliable, low-cost crawling with AI extraction, choose Spider Cloud. If you need to enforce output formats and compose multi-step LLM queries, choose LMQL.

Lmql
Lmql

LMQL is a programming language for LLM interaction with typed constraints, nested queries, and multi-backend portability.

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Spider Cloud
Spider Cloud

AI web scraping API: crawl, scrape, search any site into markdown or JSON at 10k req/min.

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Pricing
Free
Freemium
Plans
$1/GB + $0.001/min compute
$40/mo (2 concurrency)
$6/mo
Popularity
3 views
7.5k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
WebCLIAPI
WebAPICLI
Categories
📦 LLM App Frameworks & SDKs
🌐 Web Scraping & Search APIs🖱️ Browser & Computer-Use Agents
Features
Constrained decoding (token masks, regex, length limits)
Typed variables for guaranteed output types (int, regex)
Nested queries for modular prompt programming
Python control flow (loops, branching) in prompts
Multi-backend portability (llama.cpp, OpenAI, Transformers)
Batch generation API
Chat API for conversational agents
Tool augmentation for external tool calls
Inference certificates for output verification
Output streaming
Playground IDE with execution traces
String interpolation for prompt construction
Scripted prompting with multi-part prompts
Scrape any website into markdown, JSON, or raw HTML
Full-site crawling at 100K+ pages/sec
10,000 core API requests per minute default
Web Search API: SERP + scraping + extraction in one call
/ai/search endpoint with relevance gate to skip irrelevant pages
Silk AI model: HTML-to-structured data and captcha solving on GPUs
Browser Cloud: full browser sessions over CDP
AI commands (Act, Extract, Observe) via WebSocket with AI Studio
Multiple output formats: HTML, raw, plain text, markdown, JSON, JSONL, CSV, XML
Stealth browser layer and Unblocker for anti-bot sites
Proxy pool with 215M+ residential and ISP IPs across 199+ countries
Robots.txt compliance on by default, disable per-request
data_connectors parameter: pipe results to S3, GCS, Google Sheets, Azure Blob, Supabase
extraction_schema parameter: AI output conforms to JSON schema
1,000+ ready-made scraper examples across 32 categories
Integrations
OpenAI
Hugging Face Transformers
llama.cpp
LangChain
LlamaIndex
CrewAI
FlowiseAI
AutoGen
Agno

Who should pick which

  • Solo founder building an AI agent
    Pick: Spider Cloud

    Because Spider Cloud provides real-time web data via a simple API with Browser AI commands and data connectors, crucial for grounding AI agents.

  • Researcher doing prompt engineering
    Pick: Lmql

    Because LMQL's constrained generation and modular prompts allow precise control over LLM outputs and experimentation.

  • Developer creating RAG pipeline
    Pick: Spider Cloud

    Because Spider Cloud can ingest web pages as markdown for vector databases, with 99.9% success rate and low cost per page.

  • Team deploying multi-backend LLM apps
    Pick: Lmql

    Because LMQL supports OpenAI, Transformers, llama.cpp, and more, enabling portable and reusable prompt logic.

  • Data scientist needing structured data from websites
    Pick: Spider Cloud

    Because Spider Cloud's AI extraction and scraper catalog target structured output from web pages.

Frequently Asked Questions

Lmql vs Spider Cloud: which should you choose?

Spider Cloud and LMQL solve different problems: Spider Cloud is a web scraping API optimized for feeding live web data into AI pipelines (with latest Browser AI commands), while LMQL is a programming language for controlling LLM output structure. If you need reliable, low-cost crawling with AI extraction, choose Spider Cloud. If you need to enforce output formats and compose multi-step LLM queries, choose LMQL.

Which tool is better for feeding web data into an LLM?

Spider Cloud is purpose-built for web crawling and provides clean markdown or JSON output for RAG pipelines.

Can LMQL do web scraping?

No, LMQL is for controlling LLM generation, not for fetching web content.

Is Spider Cloud free to use?

It has a freemium model with pay-per-usage; costs average $0.03 per 1k pages. An open-source core exists for self-hosting.

Does LMQL support web scraping?

No, LMQL focuses on constrained text generation and does not include web scraping capabilities.

Which tool integrates with LangChain?

Both Spider Cloud and LMQL integrate with LangChain and LlamaIndex.

Can I use both tools together?

Yes, you can scrape with Spider Cloud and then process the data with LMQL for constrained LLM output.

What is the latest feature of Spider Cloud?

Browser AI commands via WebSocket (Act, Extract, Observe) for live browser interaction, plus data connectors to cloud storage.

Does LMQL have any recent updates?

No recent news captured; the tool appears stable with the described features.

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Last reviewed: July 3, 2026