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Auto-sync memory 2026-04-17_21:55

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Claude Code
2026-04-17 21:55:00 +03:00
committed by Claude Code STORAI
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---
name: DGX Spark Nodes
description: dgxmain and dgxsec - DGX Spark GB10 ARM nodes with full AI stack, Ollama, LiteLLM, credentials
type: project
originSessionId: f6f70bf9-8d74-459e-a0c1-f9f2333923d4
---
## dgxmain (10.100.102.241, Tailscale 100.124.217.84)
- ARM Cortex-X925+A725, 20 cores, 122GB RAM, NVIDIA GB10 GPU
- 3.6TB NVMe (29% used)
- SSH: yohay / Biton24680#@$ (login), Biton24680#@$ (sudo)
- Ollama: running natively (systemd), port 11434
- Models: nemotron-3-super:120b, gpt-oss:120b, llama3:70b, deepseek-r1:70b, qwen3:32b, gemma3:27b, devstral:23.6b, gemma3:4b, nomic-embed-text
- LiteLLM proxy: port 4000, key sk-dgxmain-litellm-2026
- Docker containers: Dify stack, Open WebUI, Gitea, n8n, Portainer, Caddy, WordPress, ArangoDB, TensorRT-LLM, Kali
## dgxsec (10.100.102.240, Tailscale 100.78.185.72)
- Same hardware as dgxmain
- 3.6TB NVMe (75% used - needs cleanup)
- SSH: yohay / Biton24680#@$ (login), Biton24680#@$ (sudo)
- Docker installed but was stopped, now started
- Ollama: not yet deployed
**Why:** These are the most powerful compute nodes in the cluster. Not in K8s due to ARM compatibility issues.
**How to apply:** Use standalone Docker Compose for GPU workloads. LiteLLM on dgxmain is the unified inference API for all services.