How Much RAM Do You Actually Need for OpenClaw? A Community Hardware Guide

One of the most common questions from newcomers: "How much RAM do I need for OpenClaw?" The answer might surprise you - it depends entirely on your setup.

The Short Answer

Cloud-only (API models): 2GB RAM is plenty With browser automation: 4-8GB recommended Running local models: 16GB minimum, 32-64GB+ ideal

Real-World Examples from the Community

Ultra-Minimal: Raspberry Pi & AWS t4g.nano

"I am running it on raspberry pi" — @Lalit

"2gb is alright, people ran it fine on t4g.nanos so maybe even 500 megs" — @90

If you're using OpenClaw purely as an orchestration layer with cloud APIs (Anthropic, OpenAI, Google), the gateway itself is incredibly lightweight. A Raspberry Pi or $3/month AWS nano instance works fine.

Mid-Range: 8GB Gets Tight

"I ran into issues with 8gb ram already if using also docker. So outsourced the docker stuff to my unraid server" — @Casimir1904

Once you add Docker containers, browser automation, and development tools, 8GB unified RAM can hit limits. The community suggests:

• Offload Docker workloads to a separate server
• Use swap space as a buffer
• Close unnecessary applications

Comfortable: 32GB

A Mac mini with 32GB handles OpenClaw + browser automation + multiple channels comfortably. This is the sweet spot for most power users who don't need local LLMs.

Power User: 48-64GB+ for Local Models

"Curious too, just ordered a macmini with 48GB RAM" — @G-Man

"My bot runs on an old mac air with 8gb unified ram.. local models are on my mbp m4 max with 64gb unified ram" — @Casimir1904

For local inference (Ollama, LM Studio), you need substantially more:

• 7B models: 8GB VRAM/unified RAM minimum
• 13B models: 16GB+ recommended
• 70B models: 48GB+ for reasonable performance
• Mixture of Experts (MoE): 64GB+ for full capacity

Architecture Patterns

Pattern 1: Single Machine (Simple)

[OpenClaw + Everything] ← Your Laptop/Desktop

Requires: 16-32GB for cloud APIs + browser, more for local models.

Pattern 2: Split Deployment (Cost-Effective)

[OpenClaw Gateway] ← Cheap VPS / Raspberry Pi (2-4GB) ↓ [Local Models] ← Dedicated GPU server / Mac Studio

Separate your always-on gateway from resource-intensive inference.

Pattern 3: Hybrid (Production)

[OpenClaw Gateway] ← Home server / VPS ↓ [Cloud APIs] ← Claude, GPT, Gemini [Local Models] ← For specific tasks

Use cloud for most work, local for privacy-sensitive or high-volume tasks.

Quick Recommendations

Final Thoughts

Don't overbuy if you're using cloud APIs - OpenClaw's gateway is remarkably efficient. But if local inference is your goal, invest in memory (unified RAM on Apple Silicon is particularly effective for this).

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Hardware recommendations sourced from community discussions in #general and #users-helping-users on February 18, 2026.