What this error means

llama runner process has terminated: signal arrived during cgo execution is a Ollama failure pattern reported for developers trying to fix ollama llama runner crash with 'signal arrived during cgo execution' on nvidia gpu. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

Fresh GitHub issue (#16102, created 2026-05-11) on ollama/ollama. GTX TITAN X (12 GB VRAM) + CUDA 13 + Ubuntu crashes on Qwen2.5 14B with 'llama runner process has terminated: signal arrived during cgo execution'. VRAM only reaches ~1 GB before crash, ruling out OOM. 7B models load fine on same hardware.

Common causes

  • Ollama users with older NVIDIA GPUs (Maxwell architecture) and CUDA 13 drivers experience immediate crashes when loading Qwen2.5 14B models. The 7B models work fine, suggesting a backend compatibility issue with specific model sizes. Error surfaces as HTTP 500 with 'exit status 2' in Ollama logs.
  • Fresh GitHub issue (#16102, created 2026-05-11) on ollama/ollama. GTX TITAN X (12 GB VRAM) + CUDA 13 + Ubuntu crashes on Qwen2.5 14B with 'llama runner process has terminated: signal arrived during cgo execution'. VRAM only reaches ~1 GB before crash, ruling out OOM. 7B models load fine on same hardware.

Quick fixes

  1. Confirm the exact error signature matches llama runner process has terminated: signal arrived during cgo execution.
  2. Check the Ollama account, local tool state, and provider configuration involved in the failing workflow.
  3. Compare the failing environment with a known working setup, then change one configuration value at a time.

Platform/tool-specific checks

  • Verify the command, editor, extension, or API client that produced the error.
  • Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
  • Avoid deleting credentials, local model data, or project settings until the failing scope is clear.

Step-by-step troubleshooting

  1. Capture the exact error message and the command, editor action, or request that triggered it.
  2. Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
  3. Review the source evidence below and compare it with your environment.
  4. Apply one change at a time and rerun the smallest failing action.
  5. Keep the working fix documented for the team or deployment environment.

How to prevent it

  • Keep provider/tool configuration documented.
  • Record non-secret diagnostics such as tool version, provider name, model name, and command path.
  • Add a lightweight check before CI or production workflows depend on the tool.