docs: record the frank-small llama.cpp Q6_K cutover and the frank-large gufo rollback
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type: reference
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title: "frank-small on Dankclaw — llama.cpp, MiMo-V2.6-Distill-Qwen-9B Q6_K GGUF"
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description: "The active frank-small runbook — a CUDA (sm_86) build of llama.cpp master serving bartowski's MiMo-V2.6-Distill-Qwen-9B Q6_K GGUF on the RTX 3090: two native-window sessions, the asymmetric KV contract (f16 K + q8_0 V), the flash-attention dependency that comes with quantized V, the VRAM fit, and what to check when it misbehaves."
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tags:
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- llm
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- frank-small
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- dankclaw
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- llama-cpp
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- rtx3090
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- mimo
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- gguf
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- kv-cache
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timestamp: 2026-10-01
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---
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# frank-small — llama.cpp MiMo-V2.6 Q6_K (RTX 3090)
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> **ACTIVE since 2026-10-01 night.** Replaces
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> [[frank-small-sglang-mimo-v26]] (SGLang + INT8-W8A16-AutoRound safetensors,
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> same architecture). Rolled in by Frank's night order: move this endpoint to
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> the GGUF path for **asymmetric KV** — unquantized K + q8_0 V — which only
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> llama.cpp exposes per-tensor.
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## Identity
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|Field|Value|
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|---|---|
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|Endpoint|`192.168.0.143:7771`, served alias `frank-small`|
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|Runtime|llama.cpp **master** (qwen35 model support), CUDA build `sm_86`, at `/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server`|
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|Payload|`bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF` **Q6_K**, 7,793,710,624 B, sha256 `ef96d05a2ddf2cbb450d1af1ac3860ec769d3575bafa70692ee5609bda3fad7d`, at `/home/dank/models/MiMo-Q6K/`|
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|Unit|root `frank-small.service` (repo `scripts/frank-small.service`, `User=dank`, relinked), env `scripts/frank-small.env`, serve `scripts/serve-frank-small.sh`|
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|Repo pins|`tests/frank_small_unit.bats` (stub-argv seam), `deploy_llm_small` gates in `scripts/deploy-remote.sh`|
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## Shape and the KV contract
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`--ctx-size 524288 --parallel 2` — llama.cpp divides the pool across slots,
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so each session gets `n_ctx_slot = 262144`, the model's full native window
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(boot log confirms `n_slots = 2, n_ctx_slot = 262144, kv_unified = 'false'`).
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Frank's KV contract: **K unquantized (f16), V `q8_0`** —
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`--cache-type-k f16 --cache-type-v q8_0`. Two hard dependencies ride on it:
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- **`--flash-attn on` is mandatory**: quantized V exists only on the FA
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path. Without the flag the engine falls back silently and the contract
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becomes a lie. The serve script pins the trio; the bats seam pins the
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script.
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- The VRAM budget: attention KV lives in the 8 full-attention layers only
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(4 KV heads x 256 dim). K f16 ≈ 16 KiB/token, V q8_0 ≈ 8.5 KiB/token
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(34 B per 32-element block) ⇒ ~24.5 KiB/token over the 524,288-token pool
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≈ **12.6 GiB**. Weights 7.8 + KV 12.6 + compute buffers/graphs ≈
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**20.9 GiB measured** against 24.5 GiB — the "room for checkpoints" the
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order asked for. If graph capture OOMs, halve `CTX_SIZE`; never quantize
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K to fix it.
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## Client contract
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- Thinking arrives in **`reasoning_content`** (`--reasoning-format
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deepseek`) — the same field SGLang's qwen3 parser used, so `models.yml`
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`reasoningContentField` did NOT move. Live-verified 2026-10-01 22:57.
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- **Thinking is off unless the request asks**: the MiMo GGUF template
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defaults `enable_thinking` false; `models.yml` now ships
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`chat_template_kwargs: {enable_thinking: true, preserve_thinking: true}`
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in `extraBody`. A raw client that omits it gets a no-thinking answer
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(measured — this is not a fault).
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- Tools: `--jinja` + server-side tool parsing, verified
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`tool_calls` round-trip 2026-10-01 23:0x.
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- **Text-only now.** The GGUF carries no vision projector; the
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in-checkpoint tower existed only in the SGLang safetensors. `models.yml`
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`input: [text]`.
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## No spec decode (yet)
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The GGUF has no MTP tensors (same fact that killed SGLang NEXTN), and the
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cross-model DFlash draft (`/home/dank/models/DFlash-Qwen35/qwen3.5-9b-dflash-Q8_0.gguf`,
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Q8_0) is an optimization-loop candidate, not a default — `--spec-type
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draft-dflash` needs acceptance measured on this traffic first. The bats
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seam fails if a draft flag ships unannounced.
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## Build
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No ccache, CUDA 12.4 system nvcc with `--gcc-install-dir`-free gcc-13 host
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compiler (nvcc 12.4 rejects gcc ≥ 14):
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```
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cmake -B build-cuda -S . -DCMAKE_BUILD_TYPE=Release -DGGML_CUDA=ON \
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-DCMAKE_CUDA_ARCHITECTURES=86 -DCMAKE_CUDA_HOST_COMPILER=/usr/bin/gcc-13 \
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-DLLAMA_CURL=OFF -DGGML_CCACHE=OFF
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cmake --build build-cuda -j 16 --target llama-server
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```
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The SGLang venv (`/home/dank/GitPackages/sglang-cu128`) and the INT8
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AutoRound payload (`/home/dank/models/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound`)
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stay on disk as the rollback: repoint the unit's serve script and env from
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git history (`git show frank-large-gufo-q4kxl-20261001` era is BEFORE this;
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use the parent of the 2026-10-01 night swap commit).
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## When it misbehaves
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- Port 7771 dark: `journalctl -u frank-small -n 50`; the serve script
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exits 1 naming the missing file if the binary or GGUF moved.
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- `No CUDA GPUs are available`: the 3090 vanished from the bus or the UVM
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node is missing — `nvidia-modprobe -u -c=0` (the serve script runs it).
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- Requests hang at first token while `/health` is 200: both slots busy —
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two concurrent long generations are the ceiling by contract.
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- Slow decode after a CTX change: check `nvidia-smi` — swapping KV out of
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VRAM into unified memory halves the rate silently.
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