[Diffusion] modelopt diffusion fp8 support for flux1/flux2 and wan2.2 (#22365)

docs/diffusion/quantization.md

@@ -43,10 +43,47 @@ backend.
 | quant_family     | checkpoint form                                                                            | canonical CLI                                        | supported models                                             | extra dependency                      | platform / notes                                                                                                      |
 |------------------|--------------------------------------------------------------------------------------------|------------------------------------------------------|--------------------------------------------------------------|---------------------------------------|-----------------------------------------------------------------------------------------------------------------------|
 | `fp8`            | Quantized transformer component folder, or safetensors with `quantization_config` metadata | `--transformer-path` or `--transformer-weights-path` | ALL                                                          | None                                  | Component-folder and single-file flows are both supported                                                             |
+| `modelopt-fp8`   | Converted ModelOpt FP8 transformer directory or repo with `config.json`                    | `--transformer-weights-path`                         | FLUX.2, Wan2.2                                               | None                                  | Override config is read from the quantized transformer repo; `dit_cpu_offload` and `dit_layerwise_offload` are auto-disabled |
 | `nvfp4-modelopt` | NVFP4 safetensors file, sharded directory, or repo providing transformer weights           | `--transformer-weights-path`                         | FLUX.2                                                       | `comfy-kitchen` optional on Blackwell | Blackwell can use a best-performance kit when available; otherwise SGLang falls back to the generic ModelOpt FP4 path |
 | `nunchaku-svdq`  | Pre-quantized Nunchaku transformer weights, usually named `svdq-{int4\|fp4}_r{rank}-...`   | `--transformer-weights-path`                         | Model-specific support such as Qwen-Image, FLUX, and Z-Image | `nunchaku`                            | SGLang can infer precision and rank from the filename and supports both `int4` and `nvfp4`                            |
 | `msmodelslim`    | Pre-quantized msmodelslim transformer weights                                              | `--model-path`                                       | Wan2.2 family                                                | None                                  | Currently only compatible with the Ascend NPU family and supports both `w8a8` and `w4a4`                              |
 
+## ModelOpt FP8
+
+### Usage Examples
+
+ModelOpt FP8 checkpoints should be converted into an SGLang-loadable transformer
+override first, then loaded with the original base model:
+
+```bash
+sglang generate \
+  --model-path black-forest-labs/FLUX.2-dev \
+  --transformer-weights-path BBuf/flux2-dev-modelopt-fp8-sglang-transformer \
+  --prompt "A Logo With Bold Large Text: SGL Diffusion" \
+  --save-output
+```
+
+```bash
+sglang generate \
+  --model-path Wan-AI/Wan2.2-T2V-A14B-Diffusers \
+  --transformer-weights-path BBuf/wan22-t2v-a14b-modelopt-fp8-sglang-transformer \
+  --prompt "a fox walking through neon rain" \
+  --save-output
+```
+
+### Notes
+
+- `--transformer-weights-path` is the canonical flag for converted ModelOpt FP8
+  diffusion checkpoints.
+- If the override repo or local directory contains its own `config.json`,
+  SGLang reads the quantization config from that override instead of relying on
+  the base model config.
+- `dit_cpu_offload` and `dit_layerwise_offload` are automatically disabled for
+  ModelOpt FP8 checkpoints because the runtime expects the transformed FP8
+  weights to remain GPU-resident in their column-major layout.
+- To build the converted checkpoint yourself from a ModelOpt diffusers export,
+  use `python -m sglang.multimodal_gen.tools.convert_modelopt_fp8_checkpoint`.
+
 ## NVFP4
 
 ### Usage Examples