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README.md

@@ -31,13 +31,15 @@ conversion and gives you inspectable standard LoRA keys).
 
 ## Files
 
-| File | Base trunk | sha256 |
+| File | What it is | sha256 |
 |---|---|---|
-| `minimax_h3_fl2va_pdd_acc_8step_comfyui.safetensors` | MiniMax-H3 **FL2VA** | `1dce71b9…5cda0ea` |
-| `minimax_h3_ref2va_pdd_acc_8step_comfyui.safetensors` | MiniMax-H3 **Ref2VA** | `5531fa0d…bdc78a1` |
+| `minimax_h3_fl2va_pdd_acc_8step_comfyui.safetensors` | LoRA + head bank for **FL2VA** trunk | `1dce71b9…5cda0ea` |
+| `minimax_h3_ref2va_pdd_acc_8step_comfyui.safetensors` | LoRA + head bank for **Ref2VA** trunk | `5531fa0d…bdc78a1` |
+| `minimax_h3_ref2va_pdd_acc_8step_baked_int8_convrot.safetensors` | full **Ref2VA** int8-convrot checkpoint, trunk LoRA **pre-merged** — for cards that can't fully load the model ([see below](#baked-ref2va-trunk-for-cards-that-cant-fully-load-the-model)) | `fe8e58d8…cd1e111e` |
 
-Put them in `ComfyUI/models/pdd_acc/`. Pair FL2VA with an fl2va UNET, Ref2VA with ref2va
-(bf16 or int8-convrot builds both work).
+Put the LoRA files in `ComfyUI/models/pdd_acc/`. Pair FL2VA with an fl2va UNET, Ref2VA with
+ref2va (bf16 or int8-convrot builds both work). The baked checkpoint goes in
+`ComfyUI/models/diffusion_models/` instead.
 
 ## Usage (recipe is mandatory)
 
@@ -47,6 +49,39 @@ boundaries) into `SamplerCustomAdvanced`. Strengths 1.0, `nfe` 8 (4 is also offi
 other distill LoRAs (turbo); don't stack step-caching nodes. A ready-to-run workflow ships in
 the node pack's `example_workflows/`.
 
+## Baked Ref2VA trunk (for cards that can't fully load the model)
+
+`minimax_h3_ref2va_pdd_acc_8step_baked_int8_convrot.safetensors` (34 GB) is
+[Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3)'s
+`minimax_h3_ref2va_int8_convrot` checkpoint with this repo's Ref2VA trunk LoRA
+**pre-merged at strength 1.0** (dequantize → add → requantize with the same `comfy-kitchen`
+int8-convrot kernels ComfyUI itself uses; every tensor keeps its exact dtype, shape and byte
+length). The PDD head bank is **not** in this file — it stays runtime, so you still need the
+node pack and one of the LoRA files above.
+
+**Why it exists:** ComfyUI merges LoRA patches into weights only for modules that fit in
+VRAM; offloaded modules get a per-forward `lowvram patch` — the LoRA (plus a dequantize) is
+re-applied on **every step**. On cards at the VRAM edge that fixed cost is large: ~2× s/it
+at 864×480 on a 32 GB RTX 5090
+([node pack issue #4](https://github.com/Jalen-Brunson/ComfyUI-MiniMax-H3-PDD-Acc/issues/4)).
+Baking removes the patch term entirely — measured on a fully-offloaded H200: 2.44 → 2.06 s/it
+(`lowvram patches: 258 → 0`); the win grows as the card gets smaller. **If your card fully
+loads the trunk, this file buys you nothing** — use a LoRA file above on a stock trunk.
+
+**Usage:** put it in `ComfyUI/models/diffusion_models/`, load it with a plain **UNETLoader**,
+and run the exact recipe above with the Apply node's **`lora_strength` set to `0.0`**
+(baked-trunk mode: trunk patching skipped; head bank / sigmas / guards unchanged — the node's
+`info` output confirms it). Point the Apply node at the **Ref2VA** LoRA file above (it still
+supplies the head bank and the trained sigmas). Everything else is identical: SigmaShift
+12/3, the Apply node's sigmas → euler, CFG 1.0, `nfe` 8 (4 also official).
+
+**Caveats:** the merge strength is frozen into the file — for another strength, the FL2VA
+trunk, or a bf16/pruned base, `bake_pdd_trunk.py` in the node pack bakes any base yourself
+(streaming write, a few GB of RAM). On an **unbaked** trunk, `lora_strength 0.0` silently
+renders the un-distilled model with PDD heads — if unsure, check the file's safetensors
+metadata for `pdd_acc_baked: true` (full bake provenance — source shas, strength, date — is
+embedded there).
+
 ## What was converted
 
 Trunk LoRA renamed from diffusers to ComfyUI H3 keys (`diffusion_model.*.lora_A/B.weight`