feat(nh3-ml1): LFM2.5-VL-3B (llama.cpp) + VibeVoice-ASR-Streaming-1.5B (audio.cpp) utility seats

For brokkr's dataset foundry (operator-approved 2026-09-26, relayed).
- stacks/lfm-vl-seat: llama.cpp server-cuda b11176 (digest-pinned), Q5_K_M +
  mmproj Q8_0, :8030; gateway alias lfm25-vl-3b (LiteLLM restarted, 36 s).
  Positive control exact; null control shows it describes a missing image.
- stacks/vibevoice-asr-seat: audio.cpp v0.8.2-audio8-perf-hotfix (the GGUF's
  own runtime, not vibevoice.cpp) on cuda 12.8 runtime + libgomp + libsoxr,
  sha256-pinned; :8031 direct. LibriSpeech WER 3/69, RTF 0.07-0.14; ~31 s
  cold first request.

persistent-memory.md

@@ -203,6 +203,7 @@ in `servers/pfi-gx10/README.md`. → `persistent-memory.d/2026-09-24-gx10-ac-res
 
 ## Recent decisions
 
+- `[2026-09-26]` **Two dataset-foundry utility seats LIVE on nh3-ml1 (brokkr; operator approval relayed):** LFM2.5-VL-3B on llama.cpp `:8030` (gateway `lfm25-vl-3b`, LiteLLM restarted 36 s at 0039) and VibeVoice-ASR-Streaming-1.5B on **audio.cpp** `:8031`, not vibevoice.cpp as specced; the GGUF card names audio.cpp. Controls: VL read a synthetic image exactly, but hallucinates when no image is sent; ASR WER 3/69 on the bundled LibriSpeech clips. libsoxr added (linear resampling misheard a word). First ASR request ~31 s cold. Answered brokkr: the old 27B image seat (10.250.50.54:8015) was retired 09-14; baseline = gateway `image-judge` (Flash-Next).
 - `[2026-09-26]` **Coder seat STAYS on fv-ml1 (Prime).** The nh3-ml1 copy gave the same quality (teacher-forced true-code logprob diff +0.008 ± 0.019) but ran ~5× slower (64-tok FIM ~1.0 s vs 0.2 s; 63 vs 338 tok/s), and freeing 6.3 GB on fv-ml1 GPU 1 (20 GB spare) bought little. Copy removed; recipe kept in `stacks/coder-seat/`. The RTX 2000E suits embed/rerank/classify, not latency-sensitive generation. Only coder was a candidate: parakeet stays (earlier ruling), voices is a generation seat.
 - `[2026-09-25]` **nh3-ml1 LIVE after the NH3 visit (SB off, IGFX restored): driver + CT 109 + TEI, parity vs esh-ml1 indistinguishable (cos min 0.999993 = own floor; overlap@10 1.000 vs MRL-256 control 0.684), same speed; monitoring/DNS wired. Autonomous: lxc-pve 6.0.0-2 upgrade on nh3-pve (Docker-in-LXC fix #7006). Gateway routing + AMT follow-up are Prime's.** → `persistent-memory.d/2026-09-25-nh3-ml1-live.md`
 - `[2026-09-25]` **nh3-ml1 = CT 109 @ 10.100.50.80, second TEI embed/rerank backend on nh3-pve's RTX 2000E; GPU playbooks made host-generic — BUILD DEFERRED: blocked on nh3-pve Secure Boot until the NH3 visit; SB handling and gateway routing are Prime's calls.** Tracked: `7ddd116`, Current state. → `persistent-memory.d/2026-09-25-nh3-ml1-standup.md`

servers/nh3-ml1/README.md

@@ -33,6 +33,14 @@ Prime's call (recommendation: load-share; see below).
 
 VRAM ~2.7 GB for both, so ~13 GB is free.
 
+**Dataset-foundry utility seats (2026-09-26, brokkr; operator-approved):**
+- `stacks/lfm-vl-seat`: LFM2.5-VL-3B on llama.cpp, `:8030`, gateway `lfm25-vl-3b`.
+- `stacks/vibevoice-asr-seat`: VibeVoice-ASR-Streaming-1.5B on audio.cpp,
+  `:8031`, direct only.
+
+GPU total with TEI is ~7.5 of 16 GB. Both are batch workloads, which suits this
+card.
+
 **Tried and removed (2026-09-25):** a copy of the code-completion seat
 (Qwen2.5-Coder-1.5B). It gave the same quality but ran about 5× slower than on
 fv-ml1 (a 64-token FIM completion took ~1.0 s vs ~0.2 s), so it stays on fv-ml1

stacks/lfm-vl-seat/.env.example

@@ -0,0 +1,14 @@
+# lfm-vl-seat tunables (nh3-ml1). Copy to `.env` on the server.
+
+# llama.cpp CUDA server, pinned by digest: build b11176 (commit f805c57a2),
+# published 2026-09-25. Ada sm_89 is in the CUDA build's target set.
+LLAMACPP_IMAGE=ghcr.io/ggml-org/llama.cpp@sha256:1f4b9cf58982dd4d7cc497aea31b1a456ca9a3a1f94f527d317d3fdee0d60ab6
+
+VL_PORT=8030
+VL_ALIAS=lfm25-vl-3b
+VL_MODEL_FILE=LFM2.5-VL-3B-Q5_K_M.gguf
+VL_MMPROJ_FILE=mmproj-LFM2.5-VL-3B-Q8_0.gguf
+
+# 2 parallel slots sharing 16k context (8k each): room for a few images plus text.
+VL_CTX=16384
+VL_PARALLEL=2

stacks/lfm-vl-seat/README.md

@@ -0,0 +1,23 @@
+# lfm-vl-seat
+
+**LiquidAI LFM2.5-VL-3B**, a small vision-language model, on **nh3-ml1**, served
+by llama.cpp (`ghcr.io/ggml-org/llama.cpp` server-cuda, build b11176, pinned by
+digest) on `:8030`. A utility seat for brokkr's dataset foundry (image
+understanding). Operator-approved 2026-09-26, relayed by brokkr-smithy-dev.
+
+| | |
+|---|---|
+| direct | `http://10.100.50.80:8030/v1/chat/completions`, model `lfm25-vl-3b` |
+| gateway | `lfm25-vl-3b` (ana-docker:4000, `hosted_vllm/`, `supports_vision`) |
+| files | `LFM2.5-VL-3B-Q5_K_M.gguf` + **`mmproj-LFM2.5-VL-3B-Q8_0.gguf` (required for images)** from `LiquidAI/LFM2.5-VL-3B-GGUF` @ `6f730e9a2c45` |
+| VRAM | ~2.9 GB (2 slots × 8k ctx) |
+
+**Checks, 2026-09-26.**
+- Positive control: a synthetic image (red square, blue circle, the text
+  "NH3 42") was described exactly at T=0, both direct and through the gateway.
+- Speed: prefill ~800 tok/s, decode ~92 tok/s.
+- ⚠ **Null control: with no image attached it confidently describes one anyway**
+  ("a solid black background"). Callers must make sure the image actually went in.
+
+Not wired yet: `LiquidAI/LFM2.5-VL-3B-DSpark-GGUF`, a speculative-decoding
+drafter (brokkr's "optional later").

stacks/lfm-vl-seat/compose.yaml

@@ -0,0 +1,62 @@
+# lfm-vl-seat — LiquidAI LFM2.5-VL-3B (vision-language) on nh3-ml1 (CT 109 on
+# nh3-pve, RTX 2000E Ada 16 GB), llama.cpp server. Utility seat for brokkr's
+# dataset foundry (image understanding), operator-approved 2026-09-26 (relayed
+# by brokkr-smithy-dev).
+#
+#   llama-server  LFM2.5-VL-3B Q5_K_M + mmproj Q8_0 → /v1/chat/completions
+#                 (OpenAI, with image_url content parts)                 :8030
+#
+# ⚠ --mmproj is REQUIRED for image input; without it the model is text-only and
+# says nothing about it.
+# Batch work, not latency-critical: this card decodes ~5x slower than an fv-ml1
+# Blackwell (servers/nh3-ml1/README.md), which is fine for a foundry.
+#
+# Files (not in git): /opt/aimodels/gguf/lfm25-vl-3b/ from
+# LiquidAI/LFM2.5-VL-3B-GGUF @ 6f730e9a2c45.
+name: lfm-vl-seat
+services:
+  llama-server:
+    image: ${LLAMACPP_IMAGE}
+    container_name: lfm-vl
+    restart: unless-stopped
+    ports:
+      - "${VL_PORT}:8080"
+    volumes:
+      - /opt/aimodels/gguf/lfm25-vl-3b:/models:ro
+    command:
+      - -m
+      - /models/${VL_MODEL_FILE}
+      - --mmproj
+      - /models/${VL_MMPROJ_FILE}
+      - --alias
+      - ${VL_ALIAS}
+      - --host
+      - 0.0.0.0
+      - --port
+      - "8080"
+      - -ngl
+      - "999"
+      - -c
+      - "${VL_CTX}"
+      - -np
+      - "${VL_PARALLEL}"
+      - --jinja
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              device_ids: ["0"]
+              capabilities: [gpu]
+    healthcheck:
+      test: ["CMD", "curl", "-fsS", "http://localhost:8080/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 120s
+    labels:
+      - homepage.group=AI - Eval & Retrieval
+      - homepage.name=VL — LFM2.5-VL-3B (llama.cpp, nh3-ml1)
+      - homepage.icon=mdi-image-search
+      - homepage.description=Image understanding for the dataset foundry (gateway lfm25-vl-3b)
+      - homepage.href=http://10.100.50.80:${VL_PORT}

stacks/litellm/conf/config.yaml

@@ -512,6 +512,20 @@ model_list:
     model_info:
       mode: rerank
 
+  # --- lfm25-vl-3b → LiquidAI LFM2.5-VL-3B (Q5_K_M + mmproj Q8_0), llama.cpp server on
+  #     nh3-ml1 :8030 (stacks/lfm-vl-seat, 2026-09-26). Image understanding for
+  #     brokkr's dataset foundry; send images as OpenAI image_url parts. A small VLM:
+  #     with NO image attached it confidently describes one anyway (measured), so
+  #     callers must check the image actually went in. Batch-grade speed (~90 tok/s). ---
+  - model_name: lfm25-vl-3b
+    litellm_params:
+      model: hosted_vllm/lfm25-vl-3b
+      api_base: http://10.100.50.80:8030/v1
+      api_key: os.environ/VLLM_API_KEY
+    model_info:
+      mode: chat
+      supports_vision: true
+
   # --- coder-fast → Qwen2.5-Coder-1.5B (BASE), FIM code-completion seat (ana-ml2
   #     GPU1 :8020, vLLM; deep-research pick 2026-07-27). For Zed editor inline
   #     edit-predictions via the LEGACY /v1/completions endpoint with Qwen FIM

stacks/vibevoice-asr-seat/.env.example

@@ -0,0 +1,2 @@
+# vibevoice-asr-seat tunables (nh3-ml1). Copy to `.env` on the server.
+ASR_PORT=8031

stacks/vibevoice-asr-seat/Dockerfile

@@ -0,0 +1,16 @@
+# audio.cpp server (0xShug0/audio.cpp) for VibeVoice-ASR-Streaming on nh3-ml1.
+# The release's Linux CUDA build ("cuda12.8-colab") is a bare binary that needs the
+# CUDA 12 runtime libs (cudart, cublas, cufft, nccl) plus libgomp. This image
+# supplies them, plus libsoxr (without it audio.cpp falls back to linear
+# resampling for the 16k→24k step). Built locally on the host; not pushed.
+FROM nvidia/cuda:12.8.1-runtime-ubuntu22.04
+ARG AUDIOCPP_TAG=v0.8.2-audio8-perf-hotfix
+ARG AUDIOCPP_SHA256=ccfb35869d67e520801981392189a1ab8b6c829151093e0816ecd6a2d828d8c8
+RUN apt-get update && apt-get install -y --no-install-recommends libgomp1 libsoxr0 curl ca-certificates \
+ && rm -rf /var/lib/apt/lists/*
+RUN curl -fsSL -o /tmp/a.tgz "https://github.com/0xShug0/audio.cpp/releases/download/${AUDIOCPP_TAG}/audio-${AUDIOCPP_TAG}-bin-ubuntu-x64-cuda12.8-colab.tar.gz" \
+ && echo "${AUDIOCPP_SHA256}  /tmp/a.tgz" | sha256sum -c - \
+ && mkdir -p /app && tar xzf /tmp/a.tgz -C /app --no-same-owner && rm /tmp/a.tgz \
+ && chmod +x /app/audiocpp_server
+WORKDIR /app
+ENTRYPOINT ["/app/audiocpp_server"]

stacks/vibevoice-asr-seat/README.md

@@ -0,0 +1,30 @@
+# vibevoice-asr-seat
+
+**Microsoft VibeVoice-ASR-Streaming-1.5B** (Q4_K) on **nh3-ml1**, served by
+**audio.cpp** (`0xShug0/audio.cpp` v0.8.2-audio8-perf-hotfix, Linux CUDA 12.8
+build) on `:8031`, with direct access only. A utility seat for brokkr's dataset
+foundry (speech → text with inline speaker labels). Operator-approved 2026-09-26,
+relayed by brokkr-smithy-dev.
+
+- `POST /v1/audio/transcriptions`: multipart `file=@x.wav`, `model=vibevoice-asr-streaming-1.5b`.
+  Returns `{"text": " \n Speaker 0:...", "timing": {"rtf": ...}}`.
+- `POST /v1/audio/transcriptions/live?model=…&sample_rate=16000&channels=1&sample_format=s16le`
+  takes chunked raw PCM.
+- `GET /v1/models`, `GET /health`.
+
+**Why audio.cpp and not vibevoice.cpp or llama.cpp.** The
+`christopherthompson81/VibeVoice-ASR-Streaming-1.5B-GGUF` files are audio.cpp
+packages with their sidecars embedded, per the model card, so no separate
+tokenizer is needed. The release binary expects the CUDA 12 runtime libraries,
+so `Dockerfile` puts it on `nvidia/cuda:12.8.1-runtime` with a SHA-256-pinned
+download, plus `libgomp1` and **`libsoxr0`**. Without libsoxr it falls back to
+linear resampling (16k→24k), and on one clip that turned "cutter" into "country".
+
+**Checks, 2026-09-26.** On the 4 LibriSpeech clips shipped with audio.cpp, WER
+is 3/69 = 4.35%, identical across 3 reps. Two of the three errors are "I'm" vs
+"I am" normalization. RTF is 0.07–0.14. ⚠ **The first request after a start
+takes ~31 s** (CUDA graph warmup); later ones take 0.3–1 s. VRAM ~2.0 GB.
+
+The model card recommends Q8_0 (3.3 GB; its CUDA WER is 5.80% vs Q4_K's 7.25%,
+on 69 words). To switch, change `path` in `conf/server.json`, download the file,
+and recreate the container.

stacks/vibevoice-asr-seat/compose.yaml

@@ -0,0 +1,50 @@
+# vibevoice-asr-seat — Microsoft VibeVoice-ASR-Streaming-1.5B on nh3-ml1 (CT 109,
+# RTX 2000E Ada 16 GB), served by audio.cpp. Utility seat for brokkr's dataset
+# foundry (speech → text, speaker-attributed), operator-approved 2026-09-26
+# (relayed by brokkr-smithy-dev).
+#
+#   audiocpp_server  vibevoice-asr-streaming-1.5b (Q4_K)                :8031
+#     POST /v1/audio/transcriptions            (OpenAI-style, whole file)
+#     POST /v1/audio/transcriptions/live?...   (chunked 16 kHz s16le PCM)
+#     GET  /v1/models, /health
+#
+# Runtime is audio.cpp, per the GGUF's own model card (the GGUF is an audio.cpp
+# package with its sidecars embedded, so no separate tokenizer file). It is NOT
+# vanilla llama.cpp and NOT mudler's vibevoice.cpp.
+# Direct access only; no gateway entry.
+#
+# Files (not in git): /opt/aimodels/gguf/vibevoice-asr-streaming-1.5b/ from
+# christopherthompson81/VibeVoice-ASR-Streaming-1.5B-GGUF @ ff9615110299.
+name: vibevoice-asr-seat
+services:
+  audiocpp:
+    build:
+      context: .
+    image: local/audiocpp:v0.8.2-audio8-perf-hotfix
+    container_name: vibevoice-asr
+    restart: unless-stopped
+    command: ["--config", "/config/server.json", "--no-ui", "--log"]
+    ports:
+      - "${ASR_PORT}:8080"
+    volumes:
+      - /opt/aimodels/gguf/vibevoice-asr-streaming-1.5b:/models:ro
+      - /opt/docker/conf/vibevoice-asr-seat/server.json:/config/server.json:ro
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              device_ids: ["0"]
+              capabilities: [gpu]
+    healthcheck:
+      test: ["CMD", "curl", "-fsS", "http://localhost:8080/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 120s
+    labels:
+      - homepage.group=AI - Eval & Retrieval
+      - homepage.name=ASR — VibeVoice Streaming 1.5B (audio.cpp, nh3-ml1)
+      - homepage.icon=mdi-microphone-message
+      - homepage.description=Streaming speech-to-text for the dataset foundry (direct, no gateway)
+      - homepage.href=http://10.100.50.80:${ASR_PORT}/v1/models

stacks/vibevoice-asr-seat/conf/server.json

@@ -0,0 +1,15 @@
+{
+  "host": "0.0.0.0",
+  "port": 8080,
+  "backend": "cuda",
+  "threads": 6,
+  "models": [
+    {
+      "id": "vibevoice-asr-streaming-1.5b",
+      "family": "vibevoice_asr_streaming",
+      "path": "/models/vibevoice-asr-streaming-1.5b-q4_k.gguf",
+      "task": "asr",
+      "mode": "streaming"
+    }
+  ]
+}