Running Video Generation Locally on 16GB GPUs: Quantized Models Emerge as the Go-To
Multiple authors discussed how to run video generation models locally on 16GB GPUs. The consensus: pick workflows that fit 16GB VRAM, use quantized models, and install custom nodes that support them.
Confirmed
- @PurzBeats and @mxjxn give consistent advice: keep the model and VAE within VRAM, or only slightly over, to avoid severe slowdowns from memory swapping.
- @mxjxn showcased a ComfyUI project rendering video with Stable Diffusion 1.5 + AnimateDiff, and asked whether better local video-to-video solutions exist under the 16GB limit.
Why it matters
- 16GB is a common VRAM size on mainstream consumer GPUs; quantized models and VRAM-friendly workflows directly determine whether ordinary users can run video generation smoothly on local hardware.
2026-08-29 ~ 2026-08-29 · 5 related posts
Primary sources
- [source] Local Video-to-Video on 16GB GPU: SD 1.5 + AnimateDiff Workflow — mxjxn · 2026-08-29
- Tips for local video generation on 16GB VRAM — PurzBeats · 2026-08-29
- [source] Tips for local video generation on 16GB VRAM — mxjxn · 2026-08-29