docs: record FreeToken compressed-tensors FP8 loader failures; Huihui restored

Ornith per-channel aborts in expert-source resolution (nonstandard
tensor naming); HauhauCS block-fp8 128x128 aborts in _dequant_fp8_weight
(shape mismatch). modelopt block-fp8 is the only FP8 path. Log entry +
runbook quant matrix updated; dead downloads staged to host trash.

serverAppConfigs-docs/LLM/freetoken-frank-default-small.md

@@ -19,7 +19,9 @@ The `frank-default-small` service on Dankserver is served by
 expert weights in host RAM with an LRU GPU cache. Model history on this
 runtime: official `Qwen/Qwen3.6-35B-A3B-FP8` (since 2026-09-02) →
 `batsclamp/Huihui-Qwen3.6-35B-A3B-abliterated-FP8` (2026-08-30,
-same format and pool budget). The engine itself replaced the llama.cpp
+same format and pool budget; re-landed 2026-09-01 after two
+compressed-tensors FP8 candidates failed to load — see Quantization
+Compatibility). The engine itself replaced the llama.cpp
 Tiel-Coder-35B-A3B (UD-Q6_K_XL) deployment.
 
 ## Model
@@ -105,9 +107,24 @@ FreeToken v0.1.2 supports these safetensor quants for `qwen3_5_moe`:
 | NVFP4 (compressed-tensors) | 4-bit float, group_size=16, strategy=tensor_group | ✅ |
 | Per-tensor FP8 (modelopt) | scalar `weight_scale` | ✅ |
 | Per-channel FP8 (compressed-tensors) | `weight_scale: [O, 1]` | ❌ loader bug |
+| Block-fp8 128×128 (compressed-tensors) | `quant_method: "compressed-tensors"` + `block_structure: [128, 128]` | ❌ dequant shape bug |
 | Quark W8A8 INT8 | per-channel scales | ❌ loader bug |
 | GGUF | only `gemma4` arch | ❌ for qwen3_5_moe |
 
+**2026-09-01 live verification (Dankserver):** both compressed-tensors
+FP8 shapes fail on FreeToken v0.1.2, each a clean exit at load (37 GB
+fits RAM — no swap-thrash). `ornith-ai/Ornith-1.5-35B-A3B-FP8`
+(per-channel) aborts in expert-source resolution:
+`ValueError: Missing MoE expert source layers: {'gate_up': ...}` — its
+expert tensors do not follow the `mlp.experts.{N}.gate_proj/up_proj/
+down_proj` naming the MoE provider scans for.
+`lamianlbe/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive-fp8` (block
+128×128, standard naming) resolves experts but aborts in dequant:
+`RuntimeError: The size of tensor a (2048) must match the size of
+tensor b (...)` in `_dequant_fp8_weight`, which multiplies
+`weight × weight_scale` directly instead of expanding the block scales.
+modelopt block-fp8 remains the only FP8 path that loads.
+
 ## Files
 
 | File | Purpose |