---
license: mit
base_model:
- hanshanxue/WorldStereo
- Wan-AI/Wan2.1-I2V-14B-480P-Diffusers
tags:
- safetensors
- fp8
- quantized
- video
- image-to-video
- wan
- worldstereo
pipeline_tag: image-to-video
---

# WorldStereo-memory-dmd-fp8_e4m3fn_scaled

A scaled FP8 (e4m3fn) quantization of `hanshanxue/WorldStereo`'s
`worldstereo-memory-dmd` variant. Drops VRAM from **35 GB → 20 GB** so the
14B WorldStereo DiT fits resident on 24 GB consumer GPUs (3090, 4090) instead
of needing partial-load streaming.

| | bf16 source | fp8_e4m3fn_scaled (this repo) |
|---|---|---|
| Size on disk | 34.86 GB | 20.35 GB (**-41.6%**) |
| Tensors | 1799 (all BF16) | 551 FP8 + 1800 BF16 |
| Fits in 24 GB VRAM | No (needs partial_load) | **Yes (resident)** |
| Quality | reference | typical fp8_scaled drop: <1% perceptible on short clips, faint color drift / micro-detail loss possible on long sequences ([refs](#quality)) |
| Speed on Ampere (3090) | reference | same (no native fp8 matmul; weight upcast to bf16 per matmul) |
| Speed on Ada/Hopper (4090, H100) | reference | **>2x** via `torch._scaled_mm` |

## Quantization recipe (verbatim from [kijai/ComfyUI-WanVideoWrapper](https://github.com/kijai/ComfyUI-WanVideoWrapper))

For each tensor `T` in the source state-dict:

1. If `T`'s name contains any of these keywords -> **stored unchanged in BF16**:
   ```
   norm, bias, time_in, time_, patch_embedding, img_emb, modulation,
   text_embedding, adapter, add, ref_conv, audio_proj
   ```
   This keeps numerically-sensitive small tensors (norms, biases, modulation,
   I2V cross-attn projections) at full precision.

2. If `T` is `.weight` AND has rank >= 2 AND survived the exclusion check ->
   **cast to fp8_e4m3fn with per-tensor scale**:
   ```python
   FP8_MAX = 448.0
   scale = T.float().abs().amax() / FP8_MAX
   T_fp8 = (T.float() / scale).clamp(-FP8_MAX, FP8_MAX).to(torch.float8_e4m3fn)
   ```
   Stored as two tensors:
   - `<key>` (the fp8 weight)
   - `<key>.scale_weight` (bfloat16 scalar)

3. A marker tensor `scaled_fp8` (bf16 zero) is added so loaders that check
   `"scaled_fp8" in state_dict` auto-detect the scaled-fp8 format.

## Inference

At runtime the scale must be re-applied. Two paths:

### Ampere (3090) - upcast on matmul
```python
def fp8_scaled_linear(x, w_fp8, scale, bias):
    return torch.nn.functional.linear(x, w_fp8.to(x.dtype) * scale, bias)
```

### Ada/Hopper (4090, H100) - native fp8 matmul
```python
def fp8_scaled_linear_fast(x, w_fp8, scale_w, bias, base_dtype=torch.bfloat16):
    x = x.clamp(-448, 448).to(torch.float8_e4m3fn).contiguous()
    scale_in = torch.ones((), device=x.device, dtype=torch.float32)
    return torch._scaled_mm(x.view(-1, x.shape[-1]), w_fp8.t(),
                            out_dtype=base_dtype, bias=bias,
                            scale_a=scale_in, scale_b=scale_w)
```

Reference implementations:
- `kijai/ComfyUI-WanVideoWrapper/fp8_optimization.py` (fast path)
- `kijai/ComfyUI-WanVideoWrapper/nodes_model_loading.py` `_replace_linear` (slow path)

## Naming convention

This file uses **diffusers-style keys** (`blocks.0.attn1.to_q.weight`,
`blocks.0.ffn.net.0.proj.weight`), matching the original `hanshanxue/WorldStereo`
source layout. This is different from Kijai's published Wan2.1 fp8 files which
use **native Wan keys** (`blocks.0.self_attn.q.weight`). If your loader expects
native names, run a key remap (see `diffusers_to_native_wan` in
[ComfyUI-WorldStereo](https://github.com/pozzettiandrea/ComfyUI-WorldStereo)).

## What's in the file

- **549 FP8 tensors** (14.5 GB): rank-2 Linear weights only (self-attn
  Q/K/V/O, FFN projections, controlnet linears). Conv weights stay BF16:
  no scaled-fp8 Conv kernel exists in PyTorch / ComfyUI
- **1800 BF16 tensors** (5.84 GB):
  - 362 `norm` tensors (RMSNorm gains): 1.26 GB
  - 80 `add_*` tensors (I2V cross-attention to image embeddings): 4.19 GB
  - 3 `time_*` tensors (timestep MLP): 0.37 GB
  - 759 `bias` + others: ~0.02 GB
  - 551 `*.scale_weight` scalars: 1.1 MB
- 1 marker tensor `scaled_fp8`

## Quality

This recipe (Kijai's fp8_e4m3fn_scaled) is the community standard for Wan2.1
14B inference on 24 GB GPUs. Documented behavior:

- **Subjective**: indistinguishable from bf16 on most short clips (Kijai's
  own statement: *"never any difference remotely [from fp16]"* in his
  per-tensor-scaled tests).
- **Known artifacts on long clips**: faint color drift, occasional minor
  detail loss; usually not visible side-by-side without close inspection.
  References:
  - [Comfy-Org repackaged: fp8_e4m3fn vs fp8_scaled discussion](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/discussions/22)
  - [Kijai WanVideo_comfy_fp8_scaled artifacts discussion](https://huggingface.co/Kijai/WanVideo_comfy_fp8_scaled/discussions/31)
- **Round-trip on a sample 5120x5120 attention weight**: max_abs_err = 0.005
  (3.7% of the tensor's max value, ~standard for e4m3fn-scaled).

If you observe quality regressions specific to WorldStereo's camera/scene
conditioning, fall back to bf16 with partial-load streaming.

## Provenance

- **Source**: `hanshanxue/WorldStereo` (`worldstereo-memory-dmd` variant, commit `2adb716`)
- **Source base model**: `Wan-AI/Wan2.1-I2V-14B-480P-Diffusers` (Apache-2.0)
  - Verified: WorldStereo's Wan base is **frozen** (sampled tensors differ
    from upstream only at fp16->bf16 ULPs). The novel content is the 1.76 GB
    controlnet branch under `controlnet.controlnet_blocks.*` -- WorldStereo's
    camera/scene-render conditioning.
- **Quantization tool**: `cook_worldstereo_fp8.py` (in this repo)

## License

- **WorldStereo overlay**: MIT (inherited from `hanshanxue/WorldStereo`)
- **Wan2.1 base weights**: Apache-2.0 (inherited from `Wan-AI/Wan2.1-I2V-14B-480P-Diffusers`)

A NOTICE file in this repo provides Apache-2.0 attribution and a statement of
changes per section 4 of the license.

## Files

- `WorldStereo-memory-dmd-fp8_e4m3fn_scaled.safetensors` - the quantized model
- `cook_worldstereo_fp8.py` - the quantization script (reproducible)
- `config.json` - the source `worldstereo-memory-dmd` config (carries the
  scale_map, base_model path, sampling settings)
- `README.md` - this file
- `NOTICE` - Apache-2.0 attribution
- `LICENSE` - MIT (for the WorldStereo overlay portion)