Local Coding Agent
Run local CLI coding agents with Claude Code and Ollama on DGX Station (NVIDIA GB300) using qwen3.6:27b
Confirm your environment
Description: Verify the GPU is visible before installing anything.
nvidia-smi
Expected output (example): A table showing driver version and GPU(s). On DGX Station, the GPU name may appear as NVIDIA GB300 (without "Ultra"):
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 5xx.xx Driver Version: 5xx.xx CUDA Version: 12.x |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| 0 NVIDIA GB300 On | 00000000:06:00.0 Off | 0 |
...
Install or update Ollama
Description: Install Ollama or ensure it is recent enough for modern coding models.
curl -fsSL https://ollama.com/install.sh | sh
ollama --version
To install a specific version if needed:
curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION=0.15.0 sh
If Ollama is already present, simply run:
ollama --version
Expected output (example):
ollama version is 0.15.0
Pull a coding model
Description: Download the model weights to your DGX Station.
This playbook uses qwen3.6:27b with Claude Code through Ollama:
ollama pull qwen3.6:27b
Expected output (example): Progress lines followed by "success" and the model in ollama list:
ollama list
NAME ID SIZE MODIFIED
qwen3.6:27b abc123... ... 1 minute ago
Test local inference
Description: Run a quick prompt to confirm the model loads.
ollama run qwen3.6:27b
Try a prompt like:
Write a short README checklist for a Python project.
Expected output: The model replies with a short README checklist.
Exit the Ollama REPL when done: type /bye or press Ctrl+D.
Install Claude Code
Description: Install the CLI tool that will drive the local model.
curl -fsSL https://claude.ai/install.sh | bash
Verify the installation:
claude --version
Expected output (example): A version string such as claude 0.x.x or similar. If you see claude: command not found, ensure the install script added the CLI to your PATH (e.g. restart the terminal or source your shell profile); see Troubleshooting.
Increase context length (optional)
Description: Ollama defaults to a 4096 token context length. For coding agents and larger codebases, set it to 64K tokens. This increases memory usage. For more details on configuring context length and other parameters, see the Ollama documentation (context window and runtime options).
Set the context length per session in the Ollama REPL:
ollama run qwen3.6:27b
Then, in the Ollama prompt:
/set parameter num_ctx 64000
Exit when done: type /bye or press Ctrl+D.
Optional method (set globally when serving Ollama):
sudo systemctl stop ollama
OLLAMA_CONTEXT_LENGTH=64000 ollama serve
Keep this terminal open and run the next step in a new terminal.
Connect Claude Code to Ollama
Description: Launch Claude Code through Ollama with the model you pulled.
ollama launch claude --model qwen3.6:27b
Expected output: Claude Code starts and uses the local Ollama model.
Exit Claude Code when done: type /exit or press Ctrl+C.
Complete a small coding task
Description: Create a tiny repo and let Claude Code implement a function and tests.
mkdir -p ~/cli-agent-demo
cd ~/cli-agent-demo
python3 -m venv .venv
source .venv/bin/activate
python3 -m pip install -U pytest
printf 'def add(a, b):\n """Return the sum of a and b."""\n pass\n' > math_utils.py
printf 'import math_utils\n\n\ndef test_add():\n assert math_utils.add(1, 2) == 3\n' > test_math_utils.py
If Claude Code is not already running, launch it:
ollama launch claude --model qwen3.6:27b
In Claude Code, enter:
Please implement add() in math_utils.py and make sure the test passes.
Exit Claude Code when finished: type /exit or press Ctrl+C, then run the test:
python3 -m pytest -q
deactivate
Expected output should show the test passing.
Cleanup and rollback
Description: Remove the model and stop the Ollama service if you no longer need them. Remove the model first (while the Ollama server is running), then stop the service.
WARNING
The following removes the downloaded model files from disk.
1. Remove the model (Ollama must be running). Use the same name you pulled:
ollama rm qwen3.6:27b
2. Stop the Ollama service:
sudo systemctl stop ollama
Next steps
- Use larger context (e.g. 64K–198K) for big codebases.
- Use Claude Code on multi-file refactors or test-generation tasks.