Goodbye OpenClaw, Hello ZeroClaw
If there’s one AI project that has dominated recent discussions, OpenClaw is hard to ignore.
Since going open source, its GitHub stars have skyrocketed, approaching 200,000 stars and making it one of the fastest-growing projects in GitHub history.
To be fair, OpenClaw is powerful. But anyone who has actually run it knows the trade-offs:
heavy memory usage, slow startup times, and fans spinning at full speed.
While users were patiently waiting for optimizations, a different project quietly appeared—one that takes a radically different approach.
ZeroClaw: A Rust Rewrite Focused on Speed and Efficiency
ZeroClaw is a Rust-based reimplementation designed around a single goal:
extreme performance with minimal resource usage.
By leveraging Rust’s efficiency and a sandboxed execution model, ZeroClaw pushes memory usage and response latency down to the bare minimum—while also providing a more secure runtime environment.
Because of its lightweight design, ZeroClaw can be deployed almost anywhere, from local servers to low-cost cloud instances.
Key features include:
- Ultra-lightweight: Rust-powered core with near-instant startup
- Built-in security: Native sandbox isolation and pairing mechanism
- Highly modular: Core components are fully swappable
- Zero vendor lock-in: Compatible with OpenAI-style APIs and beyond
A True Performance Comparison
Put ZeroClaw side by side with OpenClaw, and the difference is immediately obvious.
Runtime memory usage:
ZeroClaw uses just 7.8 MB, nearly 200× less than OpenClaw.Startup speed:
ZeroClaw launches almost instantly—closer to running a simple system command than starting a full application.Binary size:
At only 3.4 MB, it’s ideal for environments like Raspberry Pi or low-spec cloud servers.
For anyone looking to deploy AI agents on constrained hardware, ZeroClaw feels like a purpose-built tool rather than a compromise.
A full benchmark comparison makes this even clearer.
Deploying Your First ZeroClaw Instance
Let’s walk through how to get ZeroClaw running locally.
1) Environment Setup
ZeroClaw is written entirely in Rust.
If Rust isn’t installed on your system yet, run:
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
2) Build the Release Version
Once Rust is installed, clone the repository and build the release binary:
git clone https://github.com/theonlyhennygod/zeroclaw.git
cd zeroclaw
cargo build --release
# Install to system path
cargo install --path . --force
The release build is recommended—it’s smaller and significantly faster.
3) Initial Configuration
ZeroClaw’s onboarding process is refreshingly straightforward.
Run the interactive setup:
zeroclaw onboard --interactive
You’ll be guided through three simple steps:
- Enter your LLM API key (OpenAI, Anthropic, DeepSeek, OpenRouter, and others are supported)
- Choose the platforms you want to connect (Slack, Discord, etc.)
- Set a pairing code to prevent unauthorized access
4) Start the Daemon
Launch ZeroClaw as a background service:
zeroclaw daemon
Check its status anytime with:
zeroclaw status
At this point, you have a 24/7 always-on AI assistant running locally.
Defining AI Roles with AIEOS
Beyond basic chat, one of ZeroClaw’s most interesting features is its support for AIEOS (Artificial Intelligence Entity Object Specification).
AIEOS is designed to prevent AI agents from becoming disposable, stateless tools.
Instead, it treats them as persistent digital entities—with memory, personality, and long-term identity.
Traditionally, AI “personas” are defined through long prompts.
ZeroClaw takes a different approach: persona definition at the system level using structured JSON.
Under AIEOS, an AI’s behavior is broken down into standardized dimensions:
- Identity: name, background, origin
- Psychology: cognitive weighting, MBTI traits, ethical rules
- Linguistics: writing style, verbal habits
- Motivations: core drives and long-term goals
For example, you could load an AIEOS profile for a character like Elara Vance—an illustrator and translator—and ZeroClaw immediately becomes a creative partner.
It can translate Chinese blogs into polished English and even help design visually compelling cover images.
Enabling AIEOS is simple. After defining identity.json, add:
[identity]
format = "aieos"
aieos_path = "identity.json"
Once configured, this “digital soul” becomes fully portable.
You can migrate it across any ecosystem that supports the AIEOS standard—preserving personality and memory over time.
OpenClaw vs ZeroClaw: Which Should You Choose?
By now, the obvious question is: which one makes more sense?
Having used OpenClaw extensively on a Mac mini M4, my answer is straightforward:
both are valid—depending on the scenario.
Scenario A: Home Hub & Creative Interaction → OpenClaw
If your focus is on rich human–computer interaction—TV integration, voice control, or creative features like Live Canvas—OpenClaw still shines.
Scenario B: Automation & Server Workloads → ZeroClaw
If your needs involve scheduled tasks, log monitoring, or deployment on low-spec servers, ZeroClaw is the clear winner.
Its minimal resource footprint leaves more room for actual workloads.
Why waste memory when you can run additional services instead?
Final Thoughts
We are steadily entering the Agentic AI era.
The future internet won’t be defined by isolated apps, but by countless lightweight, always-on digital workers—running everywhere.
ZeroClaw represents a shift toward industrial-grade AI agent infrastructure:
- Rust-level performance discipline
- Local-first deployment
- Scalable enough for solo builders and small teams
The signal is clear.
The next phase of AI won’t be about eloquent conversations—it will be about executing real work at the lowest possible cost.
Project: https://github.com/theonlyhennygod/zeroclaw
Website: https://zeroclaw.bot/
That’s all for today.
Thanks for reading—and see you next time. Respect.
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