# ana-ml2

Primary AI inference host for PFI.

## Network

- **LAN IP:** 10.250.50.54 (in-band, OS-side)
- **BMC (OOB):** 10.250.250.50 — Supermicro IPMI web UI
  at <https://10.250.250.50> (homepage card: *PFI-ANA-ML2 BMC*)
- **SSH:** standard port 22 on 10.250.50.54

## Hardware

- **Chassis:** Supermicro mid-range inferencing server (bare metal,
  NOT Dell / not the same box as sf-r630 / sfsrv-ana)
- **CPU:** AMD EPYC 9254 24-core (96 threads)
- **RAM:** 566 GB
- **GPUs:** 2x NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition (96 GB VRAM each, cc 12.0 / sm_120, GPU 0 and GPU 1) — upgraded 2026-06 from 2x RTX 6000 Ada (46 GB, cc 8.9). Blackwell adds native FP4 (NVFP4) tensor cores and doubles VRAM.
- **Storage:** ZFS `zroot` (434 GB root) + `tank` pool (8.6 TB at `/tank`)
- **OS:** Debian 13 (trixie), kernel 6.12.x
- **Docker:** 29.3.1, runtimes: runc (default), nvidia, io.containerd.runc.v2

## Key paths

| Path | Purpose |
|------|---------|
| `/opt/docker/compose/<stack>/` | Compose files |
| `/opt/docker/conf/<stack>/` | Config bind mounts |
| `/tank/aimodels/huggingface/` | HF cache (267 GB, pre-downloaded models) |
| `/tank/aimodels/llm/` | Legacy GGUF models (790 GB, referenced by llama-swap as `/models/`) |
| `/var/lib/docker/` | Docker data (on zroot) |

## Running stacks

Live inventory as of 2026-07-22. Each model is its own compose stack now
(container `vllm-<x>` / `llama-<x>`); the `vllm` stack proper is just the
embed/rerank/reward trio. GPUs are pinned per container via
`deploy.resources.reservations.devices[].device_ids`.

**GPU 0 — heavy RP / reasoning seats (~88/98 GB, hot serving path):**

| Container | Port | Served model | Quant | Ctx |
|-----------|------|--------------|-------|-----|
| `vllm-gen` (project `gen-seat`) | 8015 | `qwen3.8-27b-uncensored` — the "gen" hero seat (Qwen3.8-27B Heretic-abliterated, in-house NVFP4 W4A16 + grafted MTP) | NVFP4 W4A16 (compressed-tensors) | 262k |
| `vllm-charrp-reasoning-nvfp4` | 8018 | `char-rp-reasoning` (R36 reasoning RP) | NVFP4 (modelopt) | 256k |

**GPU 1 — light / eval / retrieval + char-RP GGUF (~91/98 GB, on-demand):**

| Container | Port | Served model | Quant | Ctx |
|-----------|------|--------------|-------|-----|
| `vllm-granite` | 8004 | `granite-4.1-8b` — fleet summarizer/classifier | FP8 (compressed-tensors) | 131k |
| `llama-charrp` | 8016 | `Magidonia-24B-v4.3` Q6_K — char-RP (llama.cpp) | GGUF Q6_K | — |
| ~~`vllm-selene`~~ | ~~8011~~ | **RETIRED 2026-08-23** — lost a head-to-head against `gen` on its own judge task (see `stacks/selene/README.md`); seat downed to reclaim 17.2 GiB on GPU 1. `selene-1-mini-8b` now 404s by design; use `chat-judge`. | — | — |
| `vllm-reward` | 8003 | `Skywork-Reward-V2-Llama-3.1-8B-AWQ` — reward classifier | AWQ | 16k |
| `vllm-embed` | 8001 | `Qwen3-Embedding-0.6B` | — | 8k |
| `vllm-rerank` | 8002 | `Qwen3-Reranker-0.6B` | — | 8k |

**Infra / non-GPU:**

| Container | Port | Notes |
|-----------|------|-------|
| `dockge` | 5001 | Docker stack management UI |
| `dozzle-agent` | 7007 | Log agent → Dozzle hub on ana-docker |
| `beszel-agent` | 45876 | Metrics agent → Beszel hub on ana-docker |

Both cards run near-full (~7–10 GB headroom each) — adding a seat means placing
it on the card with room or evicting a dormant one first.

**Dormant (compose present on disk, containers stopped)** — rollback / audition
seats, safe to leave: `mistral-medium-3.5`, `mistral-small-4(-heretic)`,
`ms32-24b-angel`, `qwen3.5-122b`, `qwopus3.5-122b`, `qwen35-vl`, `qwen36-vl`,
`qwen36-27b-aeon`, `qwen-image-bench`, `vibevoice`, `comfyui`, `kokoro`,
`parakeet`, `vllm-qwen3`.

**Retired:**
- `llama-swap` (former GGUF multiplexer on :9292) — replaced by dedicated
  per-model seats (e.g. `llama-charrp`); no longer running.
- `infinity` — replaced by the `vllm` stack (originally `vllm-qwen3`, renamed 2026-05-13 when the stack expanded beyond Qwen3) after the upstream Infinity image stopped shipping a `transformers` build that knew Qwen3.
- `LibreChat (+ rag_api, vectordb, mongodb, meilisearch)`, `searxng` — removed from this host (searxng now on ana-docker fleet-wide).

## Refresh state

```bash
scripts/refresh-server-info.sh ana-ml2
```

Latest snapshot: `system-details.txt` (regenerate as needed).

## GPU allocation policy

Every seat is explicitly pinned via `device_ids` (no unpinned containers), and
both cards run ~90% full:

- **GPU 0:** the two heavy NVFP4 seats — `vllm-gen` (gen) and
  `vllm-charrp-reasoning-nvfp4`. The live serving path (near-100% util under
  load), ~42 + 45 GB.
- **GPU 1:** everything else — reward,
  embed, rerank, and the Magidonia char-RP GGUF seat. Bursty/on-demand, idle
  between calls, ~91 GB resident.

Pin with `deploy.resources.reservations.devices[].device_ids: ["<id>"]` in
compose. Each service caps its share with `--gpu-memory-utilization`; with both
cards near-full, placing a new seat means freeing room (evict a dormant one) or
trimming a neighbour's utilization first.
