feat(char-rp): swap the seat to the Gemma-4 26B-A4B MoE, NVFP4, same port

Straight-across replacement of the dense G4-MeroMero-v2-31B-NVFP4A16 seat with
google/gemma-4-26B-A4B-it on ana-ml2 GPU0. Port, served-model-names and every
gateway route are unchanged, so no consumer sees a difference in addressing:
`char-rp` -> hosted_vllm/char-rp and `char-rp-reasoning` ->
hosted_vllm/char-rp-thinking, both still :8016. The seat's requirements now
include chain-of-thought, which makes throughput more critical rather than less
— the user waits through the whole reasoning block before the first visible
token, and the MoE measures ~114 tok/s @32K against the dense 31B's ~40.7.

Both artifacts are on disk and they are NOT interchangeable. The BF16 weights
(/tank/aimodels/gemma4-26b-a4b-it-bf16, 49 GB) are the QLoRA tuning base, since
QLoRA does its own quantization. They CANNOT be served here: 48.10 GiB of
weights against ~49 GiB of free GPU0 leaves nothing for KV cache, and the
engine would die at allocation exactly the way the predecessor did this
afternoon. The serving copy is RedHatAI/gemma-4-26B-A4B-it-NVFP4 (16 GB),
chosen over the other -it quants because it is compressed-tensors
(nvfp4-pack-quantized) — the same loader path the outgoing seat used — from the
llm-compressor team at 357k downloads. The nvidia/ repo is the base rather than
-it, and the thinking channel lives in the instruction-tuned weights.

Smaller weights at the same 0.47 memory budget buy a much larger KV pool:
27.37 GiB and 1,724,110 tokens, against the predecessor's 371,023 at the same
budget. That is 6.5 full-length 262K sequences concurrent rather than 1.4.

The gemma4 tool-call parser, reasoning parser and the enable_thinking:false
default all carry over unchanged — they are architecture-level, not
checkpoint-level. The --chat-template override does NOT carry over: MeroMero
pointed at a jinja hand-patched against that checkpoint, and this model ships
its own. Verified that dropping it did not reintroduce the failure that flag
existed to prevent — non-thinking prose lands in content with reasoning_content
empty, and the thinking alias populates reasoning_content with content
carrying the answer.

⚠ Scheme differs from the incumbent and the bench should say so: this quant
declares 4-bit input activations (W4A4) where the outgoing seat was NVFP4A16.
Faster, and not like-for-like on the activation axis.

meromero-charrp is retained stopped in `created` state and relabelled to
AI - Dormant, per the house rollback pattern. Both stacks want :8016, so
rolling back means stopping the gemma4 seat first.

stacks/meromero-charrp/compose.yaml

@@ -86,10 +86,14 @@ services:
     networks:
       - tnet
     labels:
-      - homepage.group=AI - Inference
-      - homepage.name=char-rp (MeroMero-v2 NVFP4, multimodal)
+      # STOPPED 2026-08-24 — superseded by stacks/gemma4-charrp (gemma-4-26B-A4B
+      # -it NVFP4 MoE) on the same port and the same served-model-names. Kept as
+      # the rollback seat: `docker compose up -d vllm-meromero-rp` here after
+      # stopping the gemma4 one, since both want :8016.
+      - homepage.group=AI - Dormant
+      - homepage.name=char-rp (MeroMero-v2 NVFP4) — rollback
       - homepage.icon=mdi-drama-masks
-      - homepage.description=G4-MeroMero-v2-31B NVFP4A16 non-thinking prose seat, vision-enabled, 256K (ana-ml2 GPU0)
+      - homepage.description=Superseded 2026-08-24 by the Gemma-4 26B-A4B MoE seat; dense 31B NVFP4A16, kept for rollback (ana-ml2 GPU0)
       - homepage.href=http://10.250.50.54:${MEROMERO_PORT:-8016}/docs
 
 networks: