Local LLMs vs Cloud: Privacy & Hardware Guide

What AI Companies Collect (Anthropic/Claude)

Data Type	Retention Period
API inputs/outputs	30 days, then deleted
Claude Pro/Free conversations	Until YOU delete them
Feedback (thumbs up/down)	5 years + may be used for training
Usage policy violations	2-7 years
Device info, IP, usage patterns	Collected automatically

⚠️ Key Warning: If you click thumbs up/down on a response, that entire conversation gets stored for 5 years and can be used for model training. Most users don't realize this.

What's Collected Automatically

Device type, OS, browser info
IP address (and derived location)
Usage patterns, browsing history within the service
Log files and error reports

Running Local LLMs: Real Hardware Setups

People absolutely do run local models. The r/LocalLLaMA community has 300k+ members.

Hardware Options by Budget

Budget	Hardware	What It Runs
~$200-400	Raspberry Pi 5 / Old laptop	7B models only, slow
~$500	Used RTX 3090 (24GB VRAM)	70B quantized, 13B full speed
~$1,000	Mac Mini M4 24GB	13-30B models comfortably
~$1,500	Mac Mini M4 Pro 48GB	70B at decent speed
~$2,000	RTX 4090 (24GB VRAM)	Fast 70B inference
~$3,000+	Mac Studio 64-128GB	Large models, very smooth

Popular Tools

Ollama - Easiest setup, one-command install
llama.cpp - Fastest, most efficient, runs anywhere
LM Studio - Nice GUI, good for beginners
text-generation-webui - Feature-rich web interface

Model Quality vs Size

Model Size	RAM/VRAM Needed	Quality Level
7B params	8-16GB	Basic tasks, simple code
13B params	16-24GB	Decent general use
30B params	24-48GB	Good quality
70B params	48-64GB+	Approaches Claude/GPT quality

Privacy Comparison

Setup	Who Sees Your Files	Who Sees Your Prompts
Local Mac/PC	Just you	Nobody (fully private)
Cloud VPS + API	VPS provider	AI company (Anthropic/OpenAI)
Claude Pro web	N/A	Anthropic
OpenClaw + Cloud API	Just you (local)	AI company
OpenClaw + Local LLM	Just you	Nobody

Pros & Cons of Local LLMs

Pros

Complete privacy - nothing leaves your machine
No API costs after hardware purchase
Works offline
No rate limits
Full control over the model

Cons

Quality gap - Claude/GPT-4 still better for complex reasoning
High upfront hardware cost for good performance
Slower inference (especially on CPU)
Smaller context windows (8-32K vs Claude's 200K)
You manage updates and maintenance

Recommendation

For experimentation: Start with Claude Pro ($20/mo) or cloud API

For privacy-sensitive work: Invest in local setup (Mac with 48GB+ or RTX 4090)

Hybrid approach: Use local for sensitive data, cloud for complex tasks

Generated by Wren | February 2026