diff --git a/comfy/ldm/wan/ar_convert.py b/comfy/ldm/wan/ar_convert.py
deleted file mode 100644
index bec5c1014..000000000
--- a/comfy/ldm/wan/ar_convert.py
+++ /dev/null
@@ -1,70 +0,0 @@
-"""
-State dict conversion for Causal Forcing checkpoints.
-
-Handles three checkpoint layouts:
-  1. Training checkpoint with top-level generator_ema / generator keys
-  2. Already-flattened state dict with model.* prefixes
-  3. Already-converted ComfyUI state dict (bare model keys)
-
-Strips prefixes so the result matches the standard Wan 2.1 / CausalWanModel key layout
-(e.g. blocks.0.self_attn.q.weight, head.modulation, etc.)
-"""
-
-import logging
-
-log = logging.getLogger(__name__)
-
-PREFIXES_TO_STRIP = ["model._fsdp_wrapped_module.", "model."]
-
-_MODEL_KEY_PREFIXES = (
-    "blocks.", "head.", "patch_embedding.", "text_embedding.",
-    "time_embedding.", "time_projection.", "img_emb.", "rope_embedder.",
-)
-
-
-def extract_state_dict(state_dict: dict, use_ema: bool = True) -> dict:
-    """
-    Extract and clean a Causal Forcing state dict from a training checkpoint.
-
-    Returns a state dict with keys matching the CausalWanModel / WanModel layout.
-    """
-    # Case 3: already converted -- keys are bare model keys
-    if "head.modulation" in state_dict and "blocks.0.self_attn.q.weight" in state_dict:
-        return state_dict
-
-    # Case 1: training checkpoint with wrapper key
-    raw_sd = None
-    order = ["generator_ema", "generator"] if use_ema else ["generator", "generator_ema"]
-    for wrapper_key in order:
-        if wrapper_key in state_dict:
-            raw_sd = state_dict[wrapper_key]
-            log.info("Causal Forcing: extracted '%s' with %d keys", wrapper_key, len(raw_sd))
-            break
-
-    # Case 2: flat dict with model.* prefixes
-    if raw_sd is None:
-        if any(k.startswith("model.") for k in state_dict):
-            raw_sd = state_dict
-        else:
-            raise KeyError(
-                f"Cannot detect Causal Forcing checkpoint layout. "
-                f"Top-level keys: {list(state_dict.keys())[:20]}"
-            )
-
-    out_sd = {}
-    for k, v in raw_sd.items():
-        new_k = k
-        for prefix in PREFIXES_TO_STRIP:
-            if new_k.startswith(prefix):
-                new_k = new_k[len(prefix):]
-                break
-        else:
-            if not new_k.startswith(_MODEL_KEY_PREFIXES):
-                log.debug("Causal Forcing: skipping non-model key: %s", k)
-                continue
-        out_sd[new_k] = v
-
-    if "head.modulation" not in out_sd:
-        raise ValueError("Conversion failed: 'head.modulation' not found in output keys")
-
-    return out_sd