What this error means

pull gpt-oss-safeguard:120b fails with Error: EOF on aarch64 is a Ollama failure pattern reported for developers trying to fix ollama model pull failing with error: eof on arm64/aarch64 architecture. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub issue (2026-05-12) with reproducible steps on aarch64. Specific model and architecture combination. Affects server-grade AI deployment (DGX Spark).

Common causes

  • Ollama model downloads fail with Error: EOF on aarch64 (NVIDIA DGX Spark / GB10) for specific large models like gpt-oss-safeguard:120b, while smaller models work fine. This is an architecture-specific regression that blocks AI model deployment on ARM servers.
  • GitHub issue (2026-05-12) with reproducible steps on aarch64. Specific model and architecture combination. Affects server-grade AI deployment (DGX Spark).

Quick fixes

  1. Confirm the exact error signature matches pull gpt-oss-safeguard:120b fails with Error: EOF on aarch64.
  2. Check the Ollama account, local tool state, and provider configuration involved in the failing workflow.
  3. Verify the model name, local service connectivity, and network access before retrying the model pull.

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.