vh
6851ecbd0b
meromero-rp sized its KV from --gpu-memory-utilization, and vLLM's profile counts co-booting neighbours as its own non-torch memory. Three boots gave 20.37 / 26.74 / 29.04 GiB of KV, and the 2026-10-05 Docker-move restart cut GPU 1 free memory to 3,981 MiB, below intern-decision's 32k-token budget. Coder read negative KV on every co-boot. Both are now pinned, so util only gates the boot check (meromero util 0.52 -> 0.47, just above its footprint). GPU 0 plateaus at ~60 MiB free 1-2 days after a boot (Beszel), so gen-small's KV drops to 5.5 GiB (461,215 tokens, 1.76x) and parakeet-nemo stays on GPU 0 with room for its 3,840 MiB cap. GPU 3 stays clear. Applied with playbooks/fv-ml1-kv-pin-20261005.yaml: GPU 1 free 3,981 -> 11,801 MiB, GPU 0 495 -> 5,039 MiB right after boot; all nine seats healthy.
meromero-charrp — MeroMero-v2 char-rp prose seat (ana-ml2 GPU0)
The non-thinking, multimodal RP prose seat. Serves the LiteLLM char-rp alias.
- Model:
G4-MeroMero-v2-31B-NVFP4A16(Gemma-4-31B, home-quantized weight-only NVFP4A16). - Host/GPU: ana-ml2, GPU0 (co-located with
gen/ vllm-aeon-gen). - Port: :8016 → LiteLLM
char-rp. - Context: 256K (
--max-model-len 262144). Gemma-4 uses sliding-window attention → KV-efficient, ~2× concurrency at full context. - Vision: enabled (image + text).
preprocessor_config.jsonwas materialized from the model's ownprocessor_config.json(Gemma4ImageProcessor); audio is config-declared but weightless. - Tool-calling: enabled via the
gemma4parser (notqwen3_coder— that's the Qwen-family XML the other seats use). Gemma-4 emits its own native<|tool_call>call:name{...}<tool_call|>syntax.
Tool-calling — the three flags are a set, don't split them
- --tool-call-parser gemma4 # native <|tool_call> syntax; without it ANY tools request 400s
- --enable-auto-tool-choice
- --reasoning-parser gemma4 # absorbs the <|channel>…<channel|> thought markers
- --default-chat-template-kwargs '{"enable_thinking": false}' # MANDATORY, see below
Why the last one is mandatory: the gemma4 parser reads enable_thinking out of
chat_template_kwargs and defaults it to True (vllm/parser/gemma4.py:439). With True,
is_reasoning_end() returns False at a new turn, which pre-initialises the parser engine to
REASONING — so all plain RP prose lands in reasoning_content and content comes back
null, breaking every char-rp consumer. This model's chat_template.jinja:350 already
defaults enable_thinking to false, so passing it explicitly renders a byte-identical
prompt (verified across plain / tools / post-tool-response / system-prompt shapes) — it changes
nothing about generation, it only corrects the parser's state machine.
Without --reasoning-parser gemma4, the post-tool-response turn leaks a literal
<|channel>thought\n<channel|> prefix into content (upstream vllm #45834 — the chat template
leaves the prompt sitting inside an open channel block).
Verified green after the fix: tool call (streaming + non-streaming), tool-result round-trip,
plain prose in content, vision.
- Tuning:
.env—MEROMERO_GPU_MEM_UTIL=0.52(leaves ~4.6 GB GPU0 headroom),MEROMERO_MAX_MODEL_LEN=262144,MEROMERO_GPU_ID=0.
Replaces the retired char-rp-gguf (Magidonia-24B GGUF / llama.cpp) seat. The quant pipeline
lives in ana-ml2:/tank/aimodels/meromero-v2-nvfp4-work/.
Deploy
scripts/deploy-stack.sh ana-ml2 meromero-charrp # diffs vs live, prompts y/N
# on host: cp .env.example .env; docker compose up -d