What this error means
Tool calling is not streaming on macOS with MLX, causing timeout when write tool outputs large code is a Ollama failure pattern reported for developers trying to fix ollama tool calls freezing and timing out on apple silicon macs with mlx backend, specifically when generating large code outputs via write tool. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
GitHub issue #16279 on ollama/ollama (2026-05-24). On macOS + MLX backend, tool call responses are fully buffered instead of streamed — unlike CUDA backend where streaming works correctly. Causes client timeouts when tools generate large files (hundreds/thousands of lines). Affects local LLM developers on Apple Silicon. Tier 0 GitHub core API result.
Common causes
- GitHub issue #16279 on ollama/ollama (2026-05-24). On macOS + MLX backend, tool call responses are fully buffered instead of streamed — unlike CUDA backend where streaming works correctly. Causes client timeouts when tools generate large files (hundreds/thousands of lines). Affects local LLM developers on Apple Silicon. Tier 0 GitHub core API result.
Quick fixes
- Confirm the exact error signature matches
Tool calling is not streaming on macOS with MLX, causing timeout when write tool outputs large code. - Check the Ollama account, local tool state, and provider configuration involved in the failing workflow.
- 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
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- 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.