Ollama / Ollama

Ollama 500 Internal Server Error — MLX Runner Fails on Linux NVIDIA GPUs

Ollama operator on Linux with NVIDIA GPU getting MLX (Apple Silicon runner) fallback errors when pulling multi-modal models, blocking model deployment Includes evidence for Ollama troubleshooting demand.

Category
Ollama
Error signature
500 Internal Server Error: mlx runner failed: Error: failed to initialize MLX — ollama pulling x/z-image-turbo model on Rocky Linux 9.7 with NVIDIA RTX 4000 SFF Ada
Quick fix
Verify the model name, local service connectivity, and network access before retrying the model pull.
Updated

What this error means

500 Internal Server Error: mlx runner failed: Error: failed to initialize MLX — ollama pulling x/z-image-turbo model on Rocky Linux 9.7 with NVIDIA RTX 4000 SFF Ada is a Ollama failure pattern reported for developers trying to ollama operator on linux with nvidia gpu getting mlx (apple silicon runner) fallback errors when pulling multi-modal models, blocking model deployment. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub issue in ollama/ollama (#16204) created 2026-05-17: running Ollama 0.24.0 on Rocky Linux 9.7 with NVIDIA RTX 4000 SFF Ada, pulling x/z-image-turbo model triggers MLX runner initialization failure. Developer had to set OLLAMA_GPU_RUNNER=cuda as workaround. Clear error signature, recent (yesterday), relevant for self-hosted LLM ops with commercial implications.

Common causes

Quick fixes

  1. Confirm the exact error signature matches 500 Internal Server Error: mlx runner failed: Error: failed to initialize MLX — ollama pulling x/z-image-turbo model on Rocky Linux 9.7 with NVIDIA RTX 4000 SFF Ada.
  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

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

Sources checked

Evidence note: GitHub issue in ollama/ollama (#16204) created 2026-05-17: running Ollama 0.24.0 on Rocky Linux 9.7 with NVIDIA RTX 4000 SFF Ada, pulling x/z-image-turbo model triggers MLX runner initialization failure. Developer had to set OLLAMA_GPU_RUNNER=cuda as workaround. Clear error signature, recent (yesterday), relevant for self-hosted LLM ops with commercial implications.

FAQ

What should I check first?

Start with the exact 500 Internal Server Error: mlx runner failed: Error: failed to initialize MLX — ollama pulling x/z-image-turbo model on Rocky Linux 9.7 with NVIDIA RTX 4000 SFF Ada text and the smallest action that reproduces it.

Can I ignore this error?

No. Treat it as a failed Ollama workflow until the root cause is understood.

Is this guaranteed to have one fix?

No. The imported evidence supports the troubleshooting path above, but tool behavior can vary by account, plan, version, provider, and local configuration.

How do I know the fix worked?

Rerun the same command, editor action, or request. The fix is working when that action completes without 500 Internal Server Error: mlx runner failed: Error: failed to initialize MLX — ollama pulling x/z-image-turbo model on Rocky Linux 9.7 with NVIDIA RTX 4000 SFF Ada.