NemoClaw vs OpenShell
Two of the top sandboxes, side by side: score, setup, license, activity and what each review found.
NemoClaw
NVIDIA reference stack running OpenClaw and Hermes inside OpenShell sandboxes
OpenShell
Policy-enforced sandbox runtime for autonomous agents with credential brokering
| What we compare | NemoClaw | OpenShell |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 62, popular | 44, known |
| Freshness | 100, active | 100, active |
| Maintenance | 76, fair | 88, healthy |
| Easy to run | 50, easy | 50, easy |
| Agent-ready | 85, ready | 85, ready |
| Facts from GitHub and the README | ||
| Stars | 22.7k | 15.8k |
| License | Apache-2.0 (permissive) | Apache-2.0 (permissive) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | None published | Oct 2026 |
| Language | Not stated | Not stated |
| Docker | Yes | Yes |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Not stated | Mentioned |
NemoClaw
CLI and installer that provision OpenShell sandboxes for OpenClaw (default), Hermes or LangChain Deep Agents Code, with guided onboarding, inference provider selection, baseline network policies with operator approval, managed integrations and persistent sandbox state. Express install targets DGX hosts and Windows WSL; a starter prompt lets Cursor, Claude Code or Codex drive setup. For personal agents with kernel-enforced isolation.
Who it is for: People running a personal agent with kernel-enforced isolation
Strengths
- Three supported agents: OpenClaw, Hermes, LangChain Deep Agents Code
- Network policy with operator approval flow and egress control from OpenShell
- Express preset install on DGX and WSL hosts
- Documented sandbox hardening: capability drops and process limits
Weaknesses
- Alpha project; maintainers review issues without guaranteed response times
- Depends on OpenShell as the runtime; details live in NVIDIA docs, not the README
- README is mostly links; no architecture or resource figures in the repo itself
- Supported platforms are limited to those on the prerequisites page
- no GPU
- Docker
- Needs NVIDIA OpenShell, Inference provider (local or routed)
- Models: providers configured through OpenShell routed inference
OpenShell
Runs each agent in a sandbox with kernel-enforced limits on file access and system calls; every outbound connection passes a policy check, and agents never see real credentials, which a gateway injects only for approved endpoints. Policy changes are checked with formal verification before approval. Installs via a shell script on Linux, Apple Silicon macOS or WSL 2; Helm for Kubernetes; SDKs for Python, TypeScript, Go and Rust.
Who it is for: Platform teams running fleets of autonomous agents
Strengths
- Credentials attached by the gateway only to approved endpoints; sandboxes never hold them
- Formal verification flags risky new access before a policy change is applied
- Kubernetes deployment via Helm; GPU use inside sandboxes documented
- Python, TypeScript, Go and Rust SDKs plus agent skills via npx skills add
Weaknesses
- Windows support is WSL 2 only and experimental
- Default sandbox image is minimal Ubuntu with no agent; running one follows the docs walkthrough
- Anonymous telemetry on by default; disable with OPENSHELL_TELEMETRY_ENABLED=false
- Kubernetes installs require a CNI that enforces NetworkPolicy
- no GPU
- Docker + Compose
- Needs Docker, Podman or host virtualization
- Models: any provider via routed inference credentials