troubleshooting

# ComfyUI Troubleshooting Guide ## Error Diagnosis Strategy When a workflow fails, follow this systematic approach: 1. **Get the error**: Use `get_history` to retrieve the execution result with full traceback 2. **Check logs**: Use `get_logs` with keyword filters like `"error"`, `"warning"`, `"traceback"` 3. **Identify the failing node**: The history response includes the `node_id` and `node_type` that failed 4. **Cross-reference inputs**: Use `get_node_info` to verify the failing node's expected input schema 5. **Check models**: Use `list_local_models` to verify all referenced model files exist ## Out of Memory (OOM) ### Error Pattern ``` torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate X MiB. GPU 0 has a total capacity of 24.00 GiB of which X MiB is free. ``` Or: ``` RuntimeError: CUDA error: out of memory ``` ### Root Cause The GPU does not have enough VRAM to hold the model weights, intermediate tensors, and latent images simultaneously. Common triggers: - High resolution images (2048x2048+) - Multiple models loaded simultaneously - FP32 precision models on limited VRAM - Video generation (LTXV, AnimateDiff) with many frames - Large batch sizes ### Fixes (in order of preference) 1. **Reduce resolution**: Drop to the model's native resolution (512 for SD 1.5, 1024 for SDXL/Flux) 2. **Use FP8/FP16 quantized models**: FP8 Flux models use ~8GB vs ~24GB for FP16 - Search for FP8 variants: `search_models("flux fp8")` or `search_models("sdxl fp8"...