Description
Description
On a DGX Spark / NVIDIA GB300 host, `nemoclaw onboard` Phase [1/8] Preflight checks prints:
✓ NVIDIA GPU detected: 1 GPU(s), 284208 MB VRAM
The output reports VRAM and GPU count but never names the GPU model. nvidia-smi on the same host reports the model correctly (NVIDIA GB300). For QA / support / docs, the GPU model is more useful identifying info than "1 GPU(s)" — and DevTest case 517913 cross-check explicitly expects format `NVIDIA GPU detected (, MB)`. The data is available to the installer (nvidia-smi --query-gpu=name --format=csv,noheader); it just isn't surfaced.
Environment
Device: DGX Spark / NVIDIA GB300 (host: galaxy-ts2-052)
OS: Ubuntu 24.04.3 LTS (Linux 6.17.0-1008-nvidia-64k)
Architecture: aarch64
Node.js: v22.22.2
npm: 10.9.7
Docker: Docker Engine 29.1.3
OpenShell CLI: openshell 0.0.36
NemoClaw: v0.0.29
OpenClaw: N/A (issue surfaces in preflight, before sandbox creation)
Steps to Reproduce
1. On a host with NVIDIA GPU, run:
curl -fsSL https://www.nvidia.com/nemoclaw.sh | bash -s -- --non-interactive --yes-i-accept-third-party-software
or:
nemoclaw onboard
2. Watch [1/8] Preflight checks output.
3. Compare with the GPU model the host actually has:
nvidia-smi --query-gpu=name --format=csv,noheader
Expected Result
Preflight prints the GPU model (and VRAM, and count if multi-GPU). Format suggested by DevTest case 517913 cross-check:
✓ NVIDIA GPU detected (NVIDIA GB300, 284208 MB)
For multi-GPU hosts, list models or summarize, e.g.:
✓ NVIDIA GPU detected: 2x NVIDIA H100 80GB, 163840 MB VRAM total
Actual Result
On the GB300 lab host:
[1/8] Preflight checks
──────────────────────────────────────────────────
✓ Docker is running
✓ Container DNS resolution works
✓ Container runtime: docker
✓ openshell CLI: openshell 0.0.36
✓ Port 8080 available (OpenShell gateway)
✓ NVIDIA GPU detected: 1 GPU(s), 284208 MB VRAM <-- model name absent
✓ Memory OK: 806139 MB RAM + 0 MB swap
Meanwhile, on the same host:
$ nvidia-smi --query-gpu=name --format=csv,noheader
NVIDIA GB300
The data is available; preflight just doesn't surface it.
Note: secondary observation — when re-running onboard with the gateway already healthy, the preflight line for port 8080 changes to "✓ Port 8080 already owned by healthy NemoClaw runtime (OpenShell gateway)" which has the same shape — useful pattern but the GPU line never adapts to provide model info even on subsequent runs.
Bug Details
| Field |
Value |
| Priority |
Unprioritized |
| Action |
Dev - Open - To fix |
| Disposition |
Open issue |
| Module |
Machine Learning - NemoClaw |
| Keyword |
NemoClaw, NemoClaw_CLI&UX, NEMOCLAW_GH_SYNC_APPROVAL, NemoClaw_Onboard |
[NVB#6126096]
Description
Description
On a DGX Spark / NVIDIA GB300 host, `nemoclaw onboard` Phase [1/8] Preflight checks prints: ✓ NVIDIA GPU detected: 1 GPU(s), 284208 MB VRAM The output reports VRAM and GPU count but never names the GPU model. nvidia-smi on the same host reports the model correctly (NVIDIA GB300). For QA / support / docs, the GPU model is more useful identifying info than "1 GPU(s)" — and DevTest case 517913 cross-check explicitly expects format `NVIDIA GPU detected (, MB)`. The data is available to the installer (nvidia-smi --query-gpu=name --format=csv,noheader); it just isn't surfaced.Environment Steps to Reproduce1. On a host with NVIDIA GPU, run: curl -fsSL https://www.nvidia.com/nemoclaw.sh | bash -s -- --non-interactive --yes-i-accept-third-party-software or: nemoclaw onboard 2. Watch [1/8] Preflight checks output. 3. Compare with the GPU model the host actually has: nvidia-smi --query-gpu=name --format=csv,noheaderExpected ResultPreflight prints the GPU model (and VRAM, and count if multi-GPU). Format suggested by DevTest case 517913 cross-check: ✓ NVIDIA GPU detected (NVIDIA GB300, 284208 MB) For multi-GPU hosts, list models or summarize, e.g.: ✓ NVIDIA GPU detected: 2x NVIDIA H100 80GB, 163840 MB VRAM totalActual ResultBug Details
[NVB#6126096]