Diffusers: Reduce memory usage guide
Source: https://huggingface.co/docs/diffusers/optimization/memory
Links to diffusers docs v0.41.0 appear on the page.
Structured fields
{
"archived": false,
"checked_at": "2026-10-17T00:00:00.000Z",
"parent_url": "https://github.com/huggingface/diffusers",
"usefulness": "Official walkthrough of sharded checkpoints, device_map placement, VAE slicing/tiling, model/sequential/group CPU offload (with CUDA streams and disk offload), layerwise fp8 casting and attention backends for running FLUX/Wan/CogVideoX-size models on limited VRAM.",
"source_type": "documentation",
"availability": "available",
"source_owner": "Hugging Face",
"next_check_at": "2026-10-24T00:00:00.000Z"
}Evidence claims
- [sourced_fact] Guide covers multiple-GPU placement (device_map balanced/auto), sharded checkpoints, VAE slicing and tiling, CPU/model/group offloading (block_level and leaf_level, use_stream, offload_to_disk_path), layerwise casting to float8 and attention backends. · locator: page text of docs v0.41.0 links source
- [sourced_fact] Guide warns CPU offloading is 'extremely slow', that group offload with streams needs about 2x the model size in CPU memory, and that Wan VAE (AutoencoderKLWan) does not support slicing or tiling. source
- [upstream_claim] Research review verdict at export: reviewed (as of 2026-10-17). Recorded by the research pipeline, not a hub review outcome; evidence.review stays unreviewed until an independent reviewer records one.
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| documentation | unknown | unknown | unknown | unknown | unknown | Docs license not stated on the page; the diffusers code repository license was not opened here. |