Lilac vs Spider Cloud
Side-by-side comparison of features, pricing, and ratings
At a glance
| Dimension | Lilac | Spider Cloud |
|---|---|---|
| Category | Decentralized GPU compute for inference & batch | Web scraping & crawling API for AI |
| Pricing Model | Paid; pay-per-token or subscription credits; batch at $1/hr H100 | Freemium; $49/mo Hobby plan; $0.03/1k pages usage |
| Core Tech | Kubernetes operator tapping idle GPUs, OpenAI-compatible API | Rust engine with AI extraction & browser automation |
| Target User | GPU suppliers monetizing spare capacity, AI devs seeking low-cost inference | AI agents, RAG pipelines, developers needing real-time web data |
| Key Integrations | Kubernetes, OpenAI SDK compatible | LangChain, LlamaIndex, S3, GCS, Supabase, Google Sheets |
| Latest Feature | Self-serve API, added GLM 5.1, Gemma 4, cache-read pricing (Apr 2026) | Browser AI commands (Act, Extract, Observe) via WebSocket (Mar 2026) |
These two tools solve completely different problems. Spider Cloud is essential for any AI pipeline that needs fresh, structured web data at scale — its Rust engine, AI extraction, and catalog of 1,000+ scrapers make it a no-brainer for RAG and agent workflows. Lilac is a specialized compute marketplace for teams that either have idle GPUs to sell or want the cheapest possible inference on frontier models. Choose based on your data bottleneck: fetching external data (Spider Cloud) vs. running models cheaply (Lilac). They can even complement each other.
AI web scraping API: crawl, scrape, search any site into markdown or JSON at 10k req/min.
Visit WebsiteWhat real users say: Lilac vs Spider Cloud
Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.
Lilac
26 mentions across 3 sources · 37% positive — critical
Hacker News, Product Hunt, Lemmy
What users praise
- • Monetizes idle GPUs that otherwise waste 30-50% capacity.
- • Pay-per-token inference with no contracts or minimums.
- • Suppliers keep 70% of revenue.
- • GPUs never leave supplier infrastructure for security.
What frustrates them
- • Zero community feedback to validate claims.
- • Name confusion with a freelancer tax tool on Product Hunt.
- • Batch jobs still in private beta.
- • Network quality and uptime unverified.
Researched Jul 3, 2026
Spider Cloud
41 mentions across 2 sources · 0% positive — critical
YouTube, Lemmy
What users praise
- • Competitive pay-as-you-go pricing at $1/GB with no expiry.
- • Default rate limit of 10,000 requests per minute is generous.
- • Broad output formats (HTML, markdown, JSON, CSV) cover diverse needs.
- • Integrated Web Search API bundles SERP and extraction for AI agents.
What frustrates them
- • No community feedback to confirm reliability or performance.
- • Self-reported metrics lack independent verification.
- • Stealth browser success may vary across real sites.
- • Potential legal risks from scraping; compliance is user's responsibility.
Researched Aug 26, 2026
Who should pick which
- RAG pipeline developerPick: Spider Cloud
Spider Cloud provides real-time web crawling with structured output and direct integrations with LangChain/LlamaIndex, ideal for feeding fresh data into vector databases. Its new Browser AI commands can also extract data from dynamic pages.
- GPU supplier with idle clustersPick: Lilac
Lilac's Kubernetes operator lets you monetize idle GPUs while they never leave your infrastructure, earning 70% of revenue. No other tool in this comparison offers supplier monetization.
- Startup needing cheap model inferencePick: Lilac
Lilac's pay-per-token or subscription credits on idle GPUs can be up to 12x cheaper than standard cloud inference. Supports multiple frontier models via OpenAI-compatible API with no minimums.
- AI agent building a web research toolPick: Spider Cloud
The Browser AI commands (Act, Extract, Observe) allow agents to interact with web pages like a human. The scraper catalog provides 1,000+ examples to kickstart development.
Frequently Asked Questions
Lilac vs Spider Cloud: which should you choose?
These two tools solve completely different problems. Spider Cloud is essential for any AI pipeline that needs fresh, structured web data at scale — its Rust engine, AI extraction, and catalog of 1,000+ scrapers make it a no-brainer for RAG and agent workflows. Lilac is a specialized compute marketplace for teams that either have idle GPUs to sell or want the cheapest possible inference on frontier models. Choose based on your data bottleneck: fetching external data (Spider Cloud) vs. running models cheaply (Lilac). They can even complement each other.
How do Spider Cloud and Lilac differ in core purpose?
Spider Cloud is a web scraping/crawling API for extracting data from websites; Lilac is a decentralized GPU network for running AI inference or batch compute. They solve separate problems.
Which is better for a RAG pipeline?
Spider Cloud directly supports RAG by fetching and structuring web content. Lilac can run the embedding or generation model but doesn't handle data collection.
Does Lilac offer a free tier?
No, Lilac is paid only (pay-per-token or subscription). There is no free usage tier.
Does Spider Cloud support self-hosting?
Yes, Spider Cloud has an open-source core available on GitHub for self-hosting. The cloud version adds features like AI Studio and Browser AI.
Can Lilac be used for training models?
Lilac is designed for inference and batch compute, not training. It offers batch container jobs but lacks training-specific infrastructure.
What models does Lilac support?
As of May 2026, Lilac supports MiniMax M2.7, M3, Kimi K2.6, GLM 5.1/5.2, Gemma 4 31B, with more being added.
Does Spider Cloud offer AI extraction?
Yes, Spider Cloud has Silk (custom AI model) and AI extraction fallback (two-phase, fast model then more capable). Also AI Studio for natural language crawling.
Which tool integrates with LangChain?
Spider Cloud integrates directly with LangChain, LlamaIndex, CrewAI, and more. Lilac is OpenAI SDK compatible, so it can be used with LangChain but not natively.
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Last reviewed: July 3, 2026