LMCache 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

DimensionLMCacheSpider Cloud
PricingFree (open-source)Freemium; average $0.03/1k pages; AI Studio add-on $6/mo
Target UsersLLM developers, enterprises optimizing inference latency/costAI agents, RAG pipelines, developers needing web data
Core FunctionKV cache caching and acceleration for LLM inferenceWeb crawling and scraping API with Rust engine
Key IntegrationsvLLM, TGILangChain, LlamaIndex, CrewAI, AI frameworks
Latest NewsNo recent newsBrowser AI commands (Act/Extract/Observe) via WebSocket (Mar 2026)
Open SourceFully open-source on GitHubCore open-source on GitHub

Spider Cloud and LMCache solve completely different problems. Stick with Spider Cloud if you need to pull fresh web data into your AI pipeline — its Rust engine and new Browser AI commands make it unbeatable for cost-effective scraping. Choose LMCache if your bottleneck is LLM inference latency: it caches KV caches to slash response times by up to 8x, and it's free. Don't cross-shop; buy both if your stack includes both data ingestion and inference.

Try LMCacheTry Spider Cloud
LMCache
LMCache

Open-source KV cache infrastructure for faster, cheaper LLM inference

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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
$0/mo
$1/GB + $0.001/min compute
$40/mo (2 concurrency)
$6/mo
Popularity
4 views
7.5k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
APICLI
WebAPICLI
Categories
🖥️ GPU Cloud & Model Inference
🌐 Web Scraping & Search APIs🖱️ Browser & Computer-Use Agents
Features
KV cache compression to support longer contexts
Cache reuse across requests to reduce prefill work
CacheBlend dynamic fusion for RAG with cached knowledge
Cache search beyond exact prefix matches
Multi-tier storage: GPU, CPU memory, local disk, and external backends
Cross-worker and cross-engine cache transfer
In-process and multiprocess deployment modes
Device-DAX byte-addressable memory integration
No-GPU starter guide for vLLM
Observability tools for tracking cache behavior
KV cache calculator for planning memory usage
Integration with vLLM and TGI inference engines
Integration with Nvidia Dynamo for distributed inference
Supported on AMD MI300X GPUs with 3–10× speedups
Backed by research from University of Chicago (CacheGen, CacheBlend)
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
vLLM
TGI
Nvidia Dynamo
Google Cloud GKE
AMD Instinct MI300X
CoreWeave AI Object Storage
Redis
PyTorch Foundation
Tensormesh
Mooncake
LangChain
LlamaIndex
CrewAI
FlowiseAI
AutoGen
Agno

What real users say: LMCache 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.

LMCache

60 mentions across 5 sources · 67% positive

Hacker News, YouTube, Bluesky, GitHub, Lemmy

What users praise

  • • Reduces time-to-first-token (TTFT) by up to 8x via KV cache reuse.
  • • Open-source with permissive license and active GitHub community.
  • • Integrates seamlessly with vLLM and HuggingFace TGI.
  • • Research-backed algorithms (CacheGen, CacheBlend) with peer-reviewed papers.

What frustrates them

  • • Streaming compression may be lossy, affecting output quality.
  • • Security vulnerability (CVE) in KV cache hash function up to 0.4.6.
  • • High number of open GitHub issues (402) indicates ongoing bugs.
  • • Setup and integration require intermediate infrastructure skills.

Researched Jul 18, 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

  • AI Agent Developer
    Pick: Spider Cloud

    Spider Cloud provides real-time web data extraction via API, including new Browser AI commands for interactive scraping. LMCache does not fetch external data.

  • LLM Inference Engineer
    Pick: LMCache

    LMCache reduces latency and cost by caching KV caches, integrating directly with vLLM/TGI. Spider Cloud offers no inference acceleration.

  • RAG Pipeline Builder
    Pick: Spider Cloud

    Spider Cloud crawls and structures documents for RAG ingestion; LMCache can later speed up inference on that data, but the primary data acquisition need is Spider Cloud.

  • Cost-conscious Startup
    Pick: LMCache

    LMCache is free and open-source, potentially cutting LLM serving bills by 8x. Spider Cloud's per-page cost is low but still a variable expense.

  • Enterprise with High Volume Scraping
    Pick: Spider Cloud

    Spider Cloud's Rust engine and data connectors (S3, GCS) support bulk, reliable scraping at $0.03/1k pages. LMCache handles a different problem.

Frequently Asked Questions

LMCache vs Spider Cloud: which should you choose?

Spider Cloud and LMCache solve completely different problems. Stick with Spider Cloud if you need to pull fresh web data into your AI pipeline — its Rust engine and new Browser AI commands make it unbeatable for cost-effective scraping. Choose LMCache if your bottleneck is LLM inference latency: it caches KV caches to slash response times by up to 8x, and it's free. Don't cross-shop; buy both if your stack includes both data ingestion and inference.

Can LMCache scrape websites?

No, LMCache is strictly for accelerating LLM inference by caching KV caches. It does not scrape or crawl web data.

Does Spider Cloud speed up LLM inference?

No, Spider Cloud is a data retrieval API; it does not affect inference speed of LLMs.

Which tool is better for RAG pipelines?

Spider Cloud feeds fresh, structured web data into the knowledge base. LMCache can then speed up responses when querying that data. Both can be complementary.

Is Spider Cloud's Browser AI available on all plans?

Browser AI commands require AI Studio add-on ($6/mo) as of March 2026.

Does LMCache require GPU?

LMCache runs on GPU servers; it caches KV caches from LLM inference, so a GPU hosting the LLM is needed.

Can I self-host Spider Cloud?

Yes, the core is open-source on GitHub; cloud version adds features like AI unblocker and managed connectors.

What integrations does LMCache have?

LMCache integrates with vLLM and TGI for seamless KV cache caching.

Does Spider Cloud support captcha solving?

Yes, via the /ai/unblocker endpoint using Silk AI model, and rotating proxies.

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Explore each tool further

LMCache
View LMCache reviewLMCache alternatives
Spider Cloud
View Spider Cloud reviewSpider Cloud alternatives

Browse these categories

Best AI GPU Cloud & Model Inference toolsBest AI Web Scraping & Search APIs toolsBest AI Browser & Computer-Use Agents tools
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Last reviewed: July 3, 2026