snapshot: NVFP4+MTP fast-seat quant recipe + failure state (gibberish, unisolated)

Captures the full pipeline recipe (graft->quant->splice->config->serve) with every
gotcha found this session, the 3 gibberish suspects, and the diagnostic ladder
(validate native-config no-MTP coherence FIRST) for a fresh session to finish the
chase. Also stages the NVFP4 scripts + 512-row calib. Recent decisions: NEO-CODE
seat swap (R36), webhook ALLOWED_HOST_LIST fix. Lessons: validate-tracer-bullet-first,
mtp-graft-dropped-at-load, gitea-204-red-herring.

services/heretic2-nvfp4-quant/splice_mtp.py

@@ -0,0 +1,42 @@
+#!/usr/bin/env python3
+"""Splice the BF16 MTP head tensors into the NVFP4-quantized output.
+
+The Qwen3_5ForConditionalGeneration model class does NOT expose the MTP head as a
+loadable module (it's a spec-decode drafting head vLLM reads separately from the
+checkpoint), so AutoModelForCausalLM.from_pretrained DROPS the top-level `mtp.*`
+state-dict keys on load — the quant output ends up with 0 mtp tensors. The working
+reference (pantheon-27b-mtp-nvfp4) keeps them by SPLICING the BF16 mtp.* tensors
+into the safetensors after quantization. This does the same: rewrites the single
+output shard to include the 15 BF16 mtp.* tensors (from the graft's model-mtp
+shard), matching pantheon's structure. (R36 fast-seat spike.)
+
+Usage: python3 splice_mtp.py <nvfp4_out_dir> <grafted_dir_with_model-mtp.safetensors>
+"""
+import sys
+
+from safetensors import safe_open
+from safetensors.torch import save_file
+
+out_dir, graft_dir = sys.argv[1], sys.argv[2]
+out_st = f"{out_dir}/model.safetensors"
+mtp_st = f"{graft_dir}/model-mtp.safetensors"
+
+# load the full quantized shard (round-trips packed/scale tensors exactly)
+tensors = {}
+with safe_open(out_st, framework="pt") as f:
+    for k in f.keys():
+        tensors[k] = f.get_tensor(k)
+n_main = len(tensors)
+
+# add the BF16 mtp.* tensors
+with safe_open(mtp_st, framework="pt") as f:
+    mtp_keys = list(f.keys())
+    for k in mtp_keys:
+        tensors[k] = f.get_tensor(k)
+
+assert not any("mtp" in k.lower() for k in list(tensors)[:n_main]), "output already had mtp?"
+print(f"main tensors: {n_main} | splicing {len(mtp_keys)} BF16 mtp tensors")
+print("mtp dtypes:", {str(tensors[k].dtype) for k in mtp_keys})
+
+save_file(tensors, out_st, metadata={"format": "pt"})
+print(f"DONE — rewrote {out_st} with {len(tensors)} tensors ({n_main} quantized + {len(mtp_keys)} BF16 mtp)")