Local Coding Agent
30 MINS
Run local CLI coding agents with Claude Code and Ollama on DGX Station (NVIDIA GB300) using qwen3.6:27b
| Symptom | Cause | Fix |
|---|---|---|
ollama: command not found | Ollama not installed or PATH not updated | Rerun curl -fsSL https://ollama.com/install.sh | sh and open a new shell |
| Model load fails with version error | Ollama is older than the model requires | Update Ollama to a current stable release. Do not pin to older versions. |
model not found in Claude Code | Model was not pulled | Run ollama pull qwen3.6:27b and retry with ollama launch claude --model qwen3.6:27b. |
connection refused to localhost:11434 | Ollama service not running | Start with ollama serve or sudo systemctl start ollama |
| Sharded GGUF model pull fails with HTTP 400 | Ollama does not support pulling sharded GGUF models from Hugging Face | Use the documented qwen3.6:27b model instead: ollama pull qwen3.6:27b. |
CUDA error: context is destroyed on a dual-GPU Station | Ollama may fail when both the GB300 and RTX PRO 6000 GPUs are visible | Run Ollama with one visible GPU. For example, set CUDA_VISIBLE_DEVICES=1 in the Ollama service environment, restart Ollama, and rerun the playbook. |
| Claude Code edit task fails through the direct Ollama endpoint | Direct endpoint wiring can fail with some Ollama/model combinations | Launch Claude Code through Ollama instead: ollama launch claude --model qwen3.6:27b. |
externally-managed-environment or Python package install fails | System Python blocks direct package installs | Create and activate a virtual environment, then install pytest inside it: python3 -m venv .venv, source .venv/bin/activate, python3 -m pip install -U pytest. |
| Slow responses or OOM | Insufficient GPU memory or fragmentation | On DGX Station (NVIDIA GB300), ensure no other heavy GPU workloads. If OOM persists, unload other models or set OLLAMA_MAX_LOADED_MODELS=1. |
claude: command not found after install | CLI not on PATH or install script did not complete | Restart the terminal or run source ~/.bashrc (or your shell profile). Check the install script output for the install path and add it to PATH. |
| Claude Code install fails (Node.js / network) | Node.js missing or install script cannot download | Ensure Node.js is installed (node --version). Run the installer with Bash: `curl -fsSL https://claude.ai/install.sh |
NOTE
DGX Station with NVIDIA GB300 provides ample GPU memory for the documented qwen3.6:27b workflow. Use OLLAMA_MAX_LOADED_MODELS=1 if you hit memory limits with multiple models.