ZeroClaw Review: OpenClaw's Speed Demon Rewrite in Rust

The knock on OpenClaw has always been performance. Its Node.js gateway, while functional, consumes 400-600 MB of memory at idle, takes 8 seconds to cold-start, and can bottleneck under heavy skill execution. ZeroClaw - a ground-up Rust rewrite by former Mozilla engineer Kai Tanaka and a team of twelve contributors - launched in early February 2026 with a simple value proposition: everything OpenClaw does, but faster, smaller, and memory-safe. After two weeks of comparative benchmarking, the numbers hold up.

The Rewrite

ZeroClaw is not a port. Tanaka and his team studied OpenClaw's architecture, identified the performance bottlenecks, and rebuilt the core from scratch in Rust. The gateway server, skill execution engine, message routing, and LLM client are all new code. What they preserved is compatibility: ZeroClaw reads OpenClaw SKILL.md files natively and connects to the same messaging platforms (Telegram, Discord, WhatsApp) through the same protocol adapters.

The project has 15,200 GitHub stars as of late February 2026 - modest compared to OpenClaw's 200,000+, but growing fast among performance-conscious users and self-hosters running agents on constrained hardware.

ZeroClaw is dual-licensed under MIT and Apache 2.0. Like OpenClaw, it requires an LLM backend, and the API costs are identical since both frameworks make the same model calls.

Performance Benchmarks

We ran ZeroClaw and OpenClaw side-by-side on identical hardware (4-core AMD EPYC, 8 GB RAM, Ubuntu 24.04) executing the same workloads. The results were consistent across three test runs:

The numbers are dramatic but not surprising. Rust's zero-cost abstractions and lack of garbage collection give ZeroClaw a structural advantage that no amount of Node.js optimization can close. The 38 MB idle memory footprint means ZeroClaw runs comfortably on a $5/month VPS - the same class of hardware where OpenClaw struggles.

Skill Compatibility

ZeroClaw parses SKILL.md files using the same YAML frontmatter specification as OpenClaw. In our testing, 4,850 of OpenClaw's 5,705 skills (85%) ran without modification. The remaining 15% failed for three reasons: reliance on Node.js-specific APIs (7%), assumptions about the gateway's internal state (5%), and skills that shell out to npm packages (3%).

ZeroClaw provides a compatibility layer called zc-compat that wraps Node.js skill execution in a sandboxed subprocess for the remaining 15%. This adds latency - about 200ms per invocation - but it means you can run your existing OpenClaw setup without porting skills. In practice, most users we spoke to migrated their core skills natively and used zc-compat as a bridge for niche ones.

The skill execution sandbox is a meaningful security improvement. ZeroClaw runs each skill in a Wasmtime-based WebAssembly sandbox by default, with configurable capability grants for filesystem access, network calls, and shell execution. This is not bulletproof - sandbox escapes exist - but it is a substantial improvement over OpenClaw's "skills can do anything" model.

What Works

Raw performance transforms the user experience. Sub-second cold starts mean ZeroClaw feels instant. The 0.8ms message routing means responses arrive as fast as the LLM can generate them, with zero perceptible framework overhead. Running 10 concurrent skills on hardware where OpenClaw would swap to disk is routine.

Memory efficiency enables new deployment scenarios. At 38 MB idle, ZeroClaw runs on Raspberry Pi hardware, shared hosting, free-tier cloud instances, and alongside other services on machines where OpenClaw would monopolize resources.

The Wasm sandbox is a genuine security improvement. Default sandboxing with explicit capability grants is the right model for executing community-contributed code. It does not solve prompt injection or API key storage, but it significantly reduces the blast radius of a malicious skill.

Rust's memory safety eliminates entire classes of bugs. No use-after-free, no buffer overflows, no null pointer dereferences in the agent runtime. For software that runs continuously with access to personal accounts, this matters.

What Does Not Work

The ecosystem is smaller. 15,200 stars and a growing but still small community means fewer tutorials, fewer forum answers, and less third-party tooling. If you hit a problem, you may be reading Rust source code rather than a Stack Overflow answer.

Configuration is less polished. ZeroClaw uses TOML configuration files that expose more internals than OpenClaw's more opinionated defaults. The documentation covers every option, but the initial setup requires more decisions. OpenClaw's one-click deploys have no ZeroClaw equivalent yet.

The browser UI is minimal. ZeroClaw ships a basic web dashboard for monitoring agent status and viewing logs, but it lacks OpenClaw's full control UI with skill management, agent configuration, and visual workflow editing. Tanaka has said a richer UI is planned for v0.5.

Some advanced OpenClaw features are missing. Multi-agent communication, the heartbeat monitoring system, and Moltbook integration are not yet implemented. ZeroClaw focuses on single-agent performance and plans to add multi-agent support in Q2 2026.

Strengths and Weaknesses

Strengths:

• 14x faster skill execution than OpenClaw
• 13x lower memory usage (38 MB vs. 487 MB at idle)
• 85% OpenClaw skill compatibility out of the box
• Wasm-based skill sandboxing by default
• Rust memory safety eliminates buffer overflow and use-after-free bugs
• Runs on $5/month VPS and Raspberry Pi hardware
• Dual MIT/Apache 2.0 license

Weaknesses:

• Smaller community (15,200 stars) with less third-party support
• No multi-agent workflows yet
• Minimal browser UI compared to OpenClaw
• Configuration requires more manual decisions
• No one-click deployment options
• 15% of OpenClaw skills need the compatibility layer
• Missing heartbeat monitoring and Moltbook integration

Verdict: 8.0/10

ZeroClaw does what rewrites are supposed to do: it takes a proven concept and rebuilds it with better engineering. The performance improvements are not incremental - they are transformational. A 14x speedup and 13x memory reduction mean ZeroClaw runs on hardware where OpenClaw cannot, responds faster than users can perceive, and handles workloads that would bring the original to its knees.

The Wasm sandbox is equally important. By defaulting to sandboxed skill execution with explicit capability grants, ZeroClaw addresses OpenClaw's most dangerous architectural flaw without sacrificing the skill ecosystem. It is not a complete security solution, but it is the right foundation.

What holds ZeroClaw back is maturity. The smaller community, missing multi-agent features, and minimal UI mean it is not yet a drop-in replacement for OpenClaw power users. But for anyone who prioritizes performance, security, or resource efficiency - and especially for self-hosters and edge deployments - ZeroClaw is already the better choice. Give it six months, and it may be the better choice for everyone.

Sources:

• ZeroClaw GitHub Repository - GitHub
• Rewriting OpenClaw in Rust: A Performance Post-Mortem - Kai Tanaka
• ZeroClaw vs. OpenClaw: Benchmark Comparison - Phoronix
• WebAssembly Sandboxing for AI Agent Skills - Bytecode Alliance