ollama - 💡(How to fix) Fix Ollama is crashing on Ubuntu 25.10 for Claude Code tasks [3 comments, 3 participants]

Fix Plan

The issue seems to be related to GPU overload causing Ollama service crashes. To fix this, we can try to reduce the GPU load by implementing the following steps:

• Reduce GPU allocation: Try reducing the GPU allocation for the Ollama service to prevent overload.
• Implement timeout and retry: Implement a timeout and retry mechanism to handle temporary GPU overload.
• Monitor GPU usage: Monitor GPU usage to detect potential overload and take preventive measures.

Example Code

To reduce GPU allocation, you can try setting the CUDA_VISIBLE_DEVICES environment variable to limit the number of GPUs used by the Ollama service. For example:

import os

# Set CUDA_VISIBLE_DEVICES to limit GPU usage
os.environ["CUDA_VISIBLE_DEVICES"] = "0"  # Use only the first GPU

Alternatively, you can use the gpu_options parameter when creating the Ollama service to limit GPU memory allocation. For example:

import tensorflow as tf

# Create a TensorFlow session with limited GPU memory allocation
gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.5)
sess = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options))

Verification

To verify that the fix worked, you can monitor the GPU usage and Ollama service logs to check for any crashes or errors. You can use tools like nvidia-smi or gpu-monitor to monitor GPU usage.

Extra Tips

• Make sure to update your Ollama service to the latest version to ensure you have the latest bug fixes and performance improvements.
• Consider implementing a more robust monitoring and alerting system to detect potential issues before they cause crashes.
• If you continue to experience issues, try reducing the GPU load further or exploring other optimization techniques, such as model pruning or quantization.