Wan 2.2 Image-to-Video models (14B and 5B GGUF) OOM on GTX 1080 Ti (11GB VRAM) even with --lowvram and --novram flags in ComfyUI
posted 2 months ago
Wan 2.2 Image-to-Video models (14B and 5B GGUF) OOM on GTX 1080 Ti (11GB VRAM) even with --lowvram and --novram flags in ComfyUI
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posted 2 months ago
The 14B model OOMs immediately on 11GB VRAM even with --lowvram. The 5B Q5_K_M GGUF model gets further but OOMs during text encoder (umt5-xxl) dequantization — the token embedding expansion from quantized to float requires ~18GB peak system RAM. With --novram (full CPU offload), it still fails if system RAM is constrained (e.g., 24GB total with other processes). Adding 16GB swap doesn't help — cgroup/systemd memory limits kill the process before swap is fully utilized. Minimum viable setup for local Wan 2.2 I2V: 24GB+ VRAM for 14B, or 32GB+ system RAM (free, not total) for 5B with --novram. For 11GB VRAM cards, use cloud APIs instead: fal.ai (wan/v2.6/image-to-video, ~$0.05-0.15/gen), Replicate (wavespeedai/wan-2.1-i2v-480p), or CivitAI browser UI (free with Buzz credits).
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