frank-zealot: cutover to Ternary-Bonsai-2 PQ2_0 with q8_0 KV

- env: Bonsai2 payload pair, CACHE_TYPE_K/V=q8_0 (f16 OOMs at 2x200,704:
  34 KiB vs 64 KiB/token over the 16 full-attention layers), measured boot
  ledger 22,664 used / 1,461 free incl. the 873 MiB mmproj that lands AFTER
  the engine fit check, q4_0 fallback rung, CRACK one-line MODEL_FILE swap
- deployer: runtime/model/mmproj gates re-keyed to the PrismML vendor build
  (the only loader for GGML tensor type 142 + prism.hadamard.* metadata)
- seam: payload trio pinned; KV argv assertions now derived from CACHE_TYPE_*
  in the env file — the wrong-var-name f16 fallback that produced the first
  failed trial window can no longer pass silently

tests/frank_zealot_unit.bats

@@ -1,13 +1,14 @@
 # Seam: the frank-zealot llama.cpp root unit on dankclaw.
-# frank-zealot is the RTX 3090 endpoint; since 2026-10-07 it serves
-# HauhauCS's Qwen3.5-9B-Uncensored-HauhauCS-Aggressive (Q6_K, qwen35 hybrid:
-# 32 layers, 8 full-attention + 24 Gated DeltaNet, no MTP tensors in the file)
-# via the CUDA (sm_86) build of llama.cpp master: TWO 200,704-token
-# conversations (--ctx-size 401408 --parallel 2), exact f16 K + f16 V under
-# flash attention, the publisher's own BF16 vision projector, and MTP off —
-# the file carries no nextn/mtp tensors, so there is no in-file head to draft
-# with. Log verbosity 4 ships so the VRAM-fit forensics (KV layout, buffer
-# sizes, graph capture) land in the journal.
+# frank-zealot is the RTX 3090 endpoint; since 2026-10-17 it serves
+# prism-ml/Ternary-Bonsai-2-27B-gguf at PQ2_0 — the ternary Bonsai-2-27B, a
+# qwen35 hybrid with 64 blocks (16 full-attention + 48 Gated DeltaNet, no
+# nextn/mtp tensors in the file) — via the PrismML fork build of llama.cpp
+# (vendor build 10754), the ONLY loader that registers the payload's custom
+# tensor type 142 and honours its prism.hadamard.* metadata: TWO 200,704-token
+# conversations (--ctx-size 401408 --parallel 2), q8_0 K + q8_0 V under flash
+# attention (f16 KV does not fit this card at this pool — the boot dies on a
+# 25,088 MiB cudaMalloc), the publisher's own Q8_0 vision projector, and MTP
+# off. Log verbosity 4 ships so the VRAM-fit forensics land in the journal.
 # This seam runs the serve script against a stub engine and asserts on the
 # argv it actually execs, so what is pinned is the command the operator gets.
 
@@ -95,10 +96,15 @@ run_stage() {
     grep -q 'FRANK_ZEALOT_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-zealot.env' "$UNIT"
 }
 
-@test "the shipped env points at the llama.cpp runtime and the Qwen3.5-9B Q6_K GGUF" {
-    # The payload path IS the endpoint's identity.
-    grep -qE '^LLAMA_BIN=/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server$' "$ENV_FILE"
-    grep -qE '^MODEL_FILE=/home/dank/models/Qwen35-9B-HauhauCS-Q6K/Qwen3\.5-9B-Uncensored-HauhauCS-Aggressive-Q6_K\.gguf$' "$ENV_FILE"
+@test "the shipped env points at the fork runtime and the Bonsai-2 PQ2_0 pair" {
+    # The payload path IS the endpoint's identity, and the runtime is part of
+    # it here: the file's custom tensor type 142 + prism.hadamard.* metadata
+    # make the PrismML build the only loader, so a retarget that moves the
+    # model but leaves the master build behind ships an endpoint that cannot
+    # load at all.
+    grep -qE '^LLAMA_BIN=/home/dank/GitPackages/llama-prism/llama-server$' "$ENV_FILE"
+    grep -qE '^MODEL_FILE=/home/dank/models/Bonsai2-PQ2_0/Ternary-Bonsai-2-27B-PQ2_0\.gguf$' "$ENV_FILE"
+    grep -qE '^MMPROJ_FILE=/home/dank/models/Bonsai2-PQ2_0/Ternary-Bonsai-2-27B-mmproj-Q8_0\.gguf$' "$ENV_FILE"
 }
 
 @test "the deployer gates on exactly the payload paths the env file ships" {
@@ -135,19 +141,23 @@ run_stage() {
     [ $((pool / slots)) -eq 200704 ]
 }
 
-@test "the KV contract is exact f16 K + f16 V, flash-attn on" {
+@test "the KV dtype pair follows the env file and flash-attn stays pinned on" {
+    # Asserted against the env rather than a literal so a retune moves one
+    # file, not two. The shipped pair is q8_0/q8_0: this payload bills
+    # 16 full-attention layers × 4 KV heads × 256 dim = 16,384 elements per
+    # token per cache, so f16/f16 would need 25,088 MiB of the 24,123 MiB card
+    # (measured: cudaMalloc OOM, engine fit 33,198 vs 23,558 free) while q8_0
+    # bills 34,816 B/token = 13,328.00 MiB at the 401,408 pool. The boot
+    # ledger, not this file, is the referee. flash-attn is not decoration:
+    # quantized V is only legal with it, and it must stay explicit so a
+    # future quant swap cannot silently fall back.
+    local env_k env_v
+    env_k="$(sed -nE 's/^CACHE_TYPE_K=(.+)$/\1/p' "$ENV_FILE")"
+    env_v="$(sed -nE 's/^CACHE_TYPE_V=(.+)$/\1/p' "$ENV_FILE")"
     serve_argv
     [ "$status" -eq 0 ]
-    # Frank, 2026-10-07: the 9B rung funds unquantized KV (the 26B MoE era
-    # shipped q8_0 V because the card was full). qwen35 bills the pool on the
-    # 8 full-attention layers only (8 × 4 KV heads × 256 dim = 8,192
-    # elements/token ⇒ 32 KiB/token at f16/f16, 12.25 GiB at the 401,408
-    # pool); the 24 DeltaNet layers cost a fixed recurrent state per slot.
-    # The boot ledger, not this file, is the referee. flash-attn stays pinned:
-    # any quantized-V fallback (q8_0 = this build's FP8 class) requires it, and
-    # the build carries GGML_CUDA_FA_ALL_QUANTS=ON.
-    [ "$(argv_value --cache-type-k)" = "f16" ]
-    [ "$(argv_value --cache-type-v)" = "f16" ]
+    [ "$(argv_value --cache-type-k)" = "$env_k" ]
+    [ "$(argv_value --cache-type-v)" = "$env_v" ]
     [ "$(argv_value --flash-attn)" = "on" ]
 }