feat: add per-model FP8 layerwise casting for VRAM reduction#8945
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Pfannkuchensack wants to merge 5 commits intoinvoke-ai:mainfrom
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feat: add per-model FP8 layerwise casting for VRAM reduction#8945Pfannkuchensack wants to merge 5 commits intoinvoke-ai:mainfrom
Pfannkuchensack wants to merge 5 commits intoinvoke-ai:mainfrom
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Add fp8_storage option to model default settings that enables diffusers' enable_layerwise_casting() to store weights in FP8 (float8_e4m3fn) while casting to fp16/bf16 during inference. This reduces VRAM usage by ~50% per model with minimal quality loss. Supported: SD1/SD2/SDXL/SD3, Flux, Flux2, CogView4, Z-Image, VAE (diffusers-based), ControlNet, T2IAdapter. Not applicable: Text Encoders, LoRA, GGUF, BnB, custom classes
Add per-model FP8 storage toggle in Model Manager default settings for both main models and control adapter models. When enabled, model weights are stored in FP8 format in VRAM (~50% savings) and cast layer-by-layer to compute precision during inference via diffusers' enable_layerwise_casting(). Backend: add fp8_storage field to MainModelDefaultSettings and ControlAdapterDefaultSettings, apply FP8 layerwise casting in all relevant model loaders (SD, SDXL, FLUX, CogView4, Z-Image, ControlNet, T2IAdapter, VAE). Gracefully skips non-ModelMixin models (custom checkpoint loaders, GGUF, BnB). Frontend: add FP8 Storage switch to model default settings panels with InformationalPopover, translation keys, and proper form handling.
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FP8 Layerwise Casting - Implementation
Summary
Add per-model
fp8_storageoption to model default settings that enables diffusers'enable_layerwise_casting()to store weights in FP8 (float8_e4m3fn) while casting to fp16/bf16 during inference. This reduces VRAM usage by ~50% per model with minimal quality loss.Supported: SD1/SD2/SDXL/SD3, Flux, Flux2, CogView4, Z-Image, VAE (diffusers-based), ControlNet, T2IAdapter.
Not applicable: Text Encoders, LoRA, GGUF, BnB, custom classes.
Related Issues / Discussions
enable_layerwise_casting()(available in diffusers 0.36.0)QA Instructions
fp8_storage: truein a model'sdefault_settings(via API or Model Manager UI)Test Matrix
fp8_storage=true- load and generatefp8_storage=true- load and generatefp8_storage=true- load and generatefp8_storage=true- load and generatefp8_storage=true- load and generatefp8_storage=true- load and generatefp8_storage=true- check qualityfp8_storage=true- load and generatefp8_storagefp8_storageis silently ignoredChecklist
What's Newcopy (if doing a release after this PR)