- name
- nexus-edge-deployer
- description
- Deploy 1-bit quantized AI models on VPS for Agent-as-a-Service with 98%
- version
- 2.1.0
- metadata
- openclaw
- emoji
- 🖥️
- homepage
- https://github.com/Shuwanito/SkillsMP/tree/main/.claude/skills/nexus-edge-deployer
- os
Edge AI Deployer
Enterprise-grade edge deployment for 1-bit quantized models (PrismML Bonsai, Microsoft BitNet) on minimal infrastructure.
Capabilities
- Deploy Bonsai 8B (1.15GB), 4B (0.57GB), and 1.7B (0.24GB) models on VPS
- Calculate AaaS unit economics: cost per agent, margin per VPS, break-even analysis
- Configure Ollama or llama.cpp for multi-tenant inference serving
- Auto-provision Hetzner CX22 (EUR 3.79/mo) via Cloud API
- Monitor fleet resource usage: RAM, CPU, tokens/sec per agent
- GDPR/HIPAA compliance via local inference (no data leaves server)
- Scale from 1 to 100+ agents across VPS fleet
Workflow
- Assess client requirements: model quality, latency, privacy, platform
- Select optimal model tier (8B for quality, 4B for balance, 1.7B for mobile)
- Provision VPS via Hetzner API with cloud-init (Ollama + model pre-loaded)
- Deploy agent with client-specific persona and capabilities
- Benchmark inference quality against full-precision baseline
- Configure monitoring, alerting, and auto-scaling rules
- Generate unit economics report: revenue, cost, margin, projections
Guidelines
- Always benchmark 1-bit model quality before deploying to production
- Maximum 3 Bonsai 8B agents per 4GB VPS (reserve 0.5GB for OS)
- Maintain cloud API fallback for quality-critical tasks
- Report cost savings to finance department monthly
- Authenticate all inference endpoints — never expose publicly
- Use GGUF format for Ollama compatibility