LMCache vs Spider Cloud

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

Analysis reviewed Live tool data as of 2026-10-18
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At a glance

DimensionLMCacheSpider Cloud
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 layer that stores, compresses, and reuses LLM key-value cache beyond GPU memory.

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Spider Cloud
Spider Cloud

Spider Cloud is a web scraping, crawling, and search API that streams live pages as markdown or JSON for AI agents and RAG pipelines.

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Pricing
Free
Freemium
Plans
$0/mo
$1/GB + $0.0001/CPU-min
From $6/mo
From $40/mo
Custom
Popularity
19 views
7.5k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
APICLI
WebAPIPluginCLIDesktop
Categories
🖥️ GPU Cloud & Model Inference
🌐 Web Scraping & Search APIs🖱️ Browser & Computer-Use Agents
Features
KV cache reuse across requests to eliminate redundant prefill work
CacheBlend dynamic fusion for non-prefix chunk reuse in RAG workflows
Tiered storage across GPU memory, CPU memory, local disk, and object storage
KV cache compression for longer contexts at higher concurrency
Raw Block NVMe tier for fast, recoverable off-GPU KV cache storage
At-rest encryption for KV cache stored outside the GPU
KV cache transfer across workers, engines, and deployment modes
In-process deployment inside vLLM, TGI, or Nvidia Dynamo
Multiprocess standalone server with process isolation and restart survival
LMCache SDK with KV-cache editing support
Observability for cache behavior, storage movement, and reuse patterns
KV cache calculator for sizing memory and deployment tiers
Pluggable external storage backends including object storage, Redis, and node-local storage
Documented SageMaker HyperPod deployment with disaggregated prefill and decode
Scrape a single page into markdown, JSON, HTML, raw, or plain text
Crawl entire sites with each page streamed as one JSONL line in order as it finishes
Web search endpoint returns SERP results plus the scraped pages behind them
Custom browser renders like a user: scripts run, lazy images load, infinite scroll reaches the end
Load protected pages through a real browser engine with geo checks, returning a 200
Run full browser sessions over WebSocket with anti-detection and rotating exits
Send AI commands (Act, Extract, Observe) over the Browser API WebSocket
Send a prompt on a scrape or crawl request and get named fields back as JSON
Two-phase AI extraction: a fast model for most pages, a stronger model for complex layouts
Provider router sends scrape and crawl requests to outside providers on your own keys
Data connectors pipe crawl results into S3, GCS, Google Sheets, Azure Blob, or Supabase
Proxy network with 215M+ residential and ISP exits in 199 countries, rotated per request
MCP server at mcp.spider.cloud for Claude Code, Codex, Cursor, and Claude Desktop
1,000+ ready-made scraper examples across 32 categories, each with working code
API responses support JSON, JSONL, CSV, and XML; up to 10,000 core API requests per minute by default
Integrations
vLLM
TGI
Nvidia Dynamo
Google Cloud GKE
AMD Instinct MI300X
CoreWeave AI Object Storage
Amazon SageMaker HyperPod
Redis
Tensormesh
LangChain
LlamaIndex
CrewAI
FlowiseAI
Langflow
Dify
Agno
MCP
Claude Code
Codex
Cursor
Claude Desktop
Amazon S3
Google Cloud Storage
Google Sheets

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 (averaged across 5 sources)

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

No verifiable community signal. We scanned public discussion on Oct 14, 2026 and found posts matching the name “Spider Cloud”, but could not establish that they are about this product rather than something else sharing its name. Rather than publish a score built on the wrong subject, we publish none.

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