Frank
5e166543fa
Runbook reshaped: 2 x 131072 no-spec identity, slot-2 arithmetic (drafter ~0.4 GiB + ubatch ~0.3 GiB bought the second 4,352 MiB KV slot), ngram-mod skipped on the recurrent-rollback law, MTP references kept (44.8-52.1% acceptance, 58.9-66.9 t/s), rollback = one revert of 812d9eb. AGENTS fleet row + section, LLM/index.md intro + entry, root index entry all flipped to the 2026-10-06 shape. 360/360 suite green; e2e gate 33/33 green at deploy.
230 lines
13 KiB
Markdown
230 lines
13 KiB
Markdown
---
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type: reference
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title: "frank-small on Dankclaw — llama.cpp, Swift-1.5-27B GSQ-RCO IQ3_S-mtp, 2 x 131072, no spec, q8_0 KV"
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description: "The active frank-small runbook (2026-10-05 evening; 2 × 131,072 no-spec since 2026-10-06) — llama.cpp master (CUDA sm_86) serving ukisai's Swift-1.5-Qwen3.8-27B GSQ-RCO IQ3_S (the -mtp file's head present but NOT drafted) on the RTX 3090: TWO 131,072-token conversations at Frank's 128k cap (the tight fit he ordered — 1,397 MiB measured free), q8_0 K + q8_0 V (llama.cpp's FP8 class), vision through the base-model projector (proven byte-identical tower), and the full slot-2 arithmetic."
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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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- gguf
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- rtx3090
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- qwen35
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- mtp
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- vision
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timestamp: 2026-10-05
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---
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# frank-small — llama.cpp Swift-1.5-27B IQ3_S-mtp, 2 × 131,072, no spec, q8_0 KV
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> **ACTIVE since 2026-10-05 (evening); TWO slots, spec OFF since
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> 2026-10-06.** A 27B replaces the 9B on the same 24 GiB card, bought by
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> Frank's explicit contract for the swap: context capped at 128k per
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> conversation, KV at FP8 class, vision on, "as many of those contexts as
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> you can" — the 2026-10-05 arithmetic answered **one**; Frank's 2026-10-06
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> order ("drop mtp, skip ngram, drop ubatch to 512, let's get 2 contexts at
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> 128k — should be a very tight fit") bought the second slot by spending
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> the drafter (~0.4 GiB) and ubatch headroom (~0.3 GiB). It fits:
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> **1,397 MiB measured free**, the old 2-3 GiB floor knowingly violated.
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> This supersedes BOTH earlier 2026-10-05 payloads: the live MiMo-V2.6 Q6_K
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> shape ([[frank-small-llama-mimo-q6k-2x200704]], now retired) and the
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> Ornith-1.5-9B Q8_0 swap that was committed (77decb5..380aafa) but never
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> deployed.
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## Identity
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| | |
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|---|---|
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| Host / device | Dankclaw (192.168.0.143), RTX 3090, 24,576 MiB |
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| Endpoint | `http://192.168.0.143:7771` — alias `frank-small`, `/v1` OpenAI surface |
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| Runtime | llama.cpp master (0.5.0-dev, commit 5fc4f3c), CUDA sm_86 build `…/llama-master/build-cuda/bin/llama-server` (`GGML_CUDA_FA_ALL_QUANTS=ON` — required for quantized V) |
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| Unit | root systemd `frank-small.service` ([`scripts/frank-small.service`](../../scripts/frank-small.service)), `User=dank`, `Restart=on-failure`, `LimitMEMLOCK=infinity` |
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| Serve script | [`scripts/serve-frank-small.sh`](../../scripts/serve-frank-small.sh), tunables [`scripts/frank-small.env`](../../scripts/frank-small.env) |
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| Weights | `/home/dank/models/Swift15-IQ3S/Swift-1.5-Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp.gguf` — ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF **IQ3_S -mtp**, 12,120,016,896 B, sha256 `9aecf1cd…` (qwen35 hybrid: 64 real layers, 16 full-attention + 48 Gated DeltaNet, native 262,144; **MTP head in the file**: blk.64.nextn.*, `nextn_predict_layers=1`) |
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| Projector | `…/Swift15-IQ3S/mmproj-Qwen3.8-27B-F16.gguf` — unsloth/Qwen3.8-27B-GGUF `mmproj-F16.gguf`, 927,607,488 B, sha256 `cbb841a9…` (27-layer ViT, 1152 hidden, `qwen3vl_merger` → 5120) |
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| Fetch | [`scripts/download-frank-small.sh`](../../scripts/download-frank-small.sh) — `-f`, byte count + LFS sha256 verified per file; both verified on the host before deploy |
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| Seam | `tests/frank_small_unit.bats` (argv assertions against a stub engine: payload path, slot geometry, KV pair, no-spec pair (absence of both flags), batch pair, projector opt-out) |
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## Why a base-model projector is legal here
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No Swift repo ships a projector — ukisai's GSQ-RCO release is
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language-model-only by their own README ("A Swift 27B vision projector has
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not been verified for this release"). The substitution is proven, not
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assumed: Swift-1.5 is an RL/OPD post-train of `Qwen/Qwen3.8-27B`, and its
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vision stack was hash-compared against the base on 2026-10-05 over HTTP
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range reads of the two BF16 repos — **333/333 visual tensor names match and
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6/6 sampled tensors are byte-identical** (merger `linear_fc1`/`linear_fc2`,
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blocks 0/13/26 attn/mlp). Swift's post-training touched text only, so the
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base projector IS the model's own projector. The mmproj header matches
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Swift's `vision_config` field-for-field (depth 27, hidden 1152, patch 16,
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merge 2, ffn 4304, 16 heads, out 5120).
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## Shape and KV contract
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`--ctx-size 262144 --parallel 2` — TWO conversations at Frank's 128k cap
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(the GSQ publisher's own benchmark protocol ran at 131,072 per stream).
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`CTX_SIZE` stays divisible by `PARALLEL`; the seam enforces it, and the
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per-slot number (`262144 / 2 = 131,072`) is the product contract —
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models.yml stays at 131,072.
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**KV at FP8 class: `q8_0` K + `q8_0` V (Frank, 2026-10-05 evening).**
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llama.cpp has no true fp8 KV dtype; q8_0 is the 8-bit class (1.0625 B/elem
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⇒ 8.5 effective bits) and the only FP8-class lever this runtime moves. The
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order supersedes the same-day f16/f16 rule, which was written for the
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Ornith 9B fit — at 64 KiB/token f16 the single 131,072 slot alone would
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cost 8.0 GiB of KV. At q8_0 the rate is **34 KiB/token** (16 attn layers ×
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4 KV heads × 256 dim × 1.0625 B, K and again V). `--flash-attn on` is
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pinned: quantized V requires it, and the build's
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`GGML_CUDA_FA_ALL_QUANTS=ON` (2026-09-17) makes the path real rather than a
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silent f16 fallback.
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**Two slots, by arithmetic and by order (2026-10-06).** The 2026-10-05
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arithmetic made ONE 131,072 slot the maximum under the 2-3 GiB floor (a
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second slot wanted +4,352 MiB of KV against 4,721 free — ~0.2 GiB left,
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far under the floor). Frank then ordered the budget spent differently:
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drop the MTP drafter (~0.4 GiB: one nextn layer of draft KV + its compute
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buffers), drop ubatch 1024→512 (~0.3 GiB, inferred from the measured 616
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MiB/doubling rung on the 9B), and take the second slot anyway — "should
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be a very tight fit", i.e. the 2-3 GiB floor is KNOWINGLY VIOLATED. The
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measured boot confirms: **22,728 used / 1,397 MiB free** (nvidia-smi
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`free` field), and a 512×512 image still answers `Red` afterwards
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(1,363 MiB after the probe), so the fit carries the vision transients.
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Compute buffers allocate at graph capture during BOOT, so a miss is loud
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and fast — the failure mode is a crash loop, not silent corruption.
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## Speculative decoding — OFF since 2026-10-06
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**Frank's order: drop MTP, skip ngram-mod too.** The MTP head ships IN the
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file — the `-mtp` GGUF carries `blk.64.nextn.{enorm,hnorm,shared_head_norm}`
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(`qwen35.nextn_predict_layers=1`, publisher RECIPE "MTP_OK verified") — and
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`--spec-type draft-mtp` loads it against the main model's own weights (no
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`--model-draft`, no second draft model — two context-backed drafters cannot
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share a process). It simply is NOT drafted with now: `SPEC_TYPE=none`
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strips BOTH speculative flags in the serve script (flags move as a set).
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**Why ngram-mod was skipped, not swapped in:** on a qwen35 hybrid, ngram
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speculation logs *"recurrent state rollback is not compatible with
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'ngram-mod' — disabling rollback support"* (fleet lesson from frank-large's
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chain measurement, 2026-10-03). A rejected draft on Gated DeltaNet layers
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cannot be rewound by KV truncation — without the rollback checkpoints the
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DeltaNet state carries phantom transitions and output degrades silently.
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MTP measured fine here (below); it was spent for the second slot, not
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abandoned for ngram.
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**Measured MTP references (2026-10-05, for the day the head returns)**,
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draft counts from the live `timings` on real-ish traffic: temp 0.8 →
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66.1 tok/s, 182/349 accepted (52.1 %); temp 0 → 66.9 tok/s, 166/318;
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deployed recipe (temp 1.0/top_p 0.95/top_k 20) → 58.9 tok/s, 159/355
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(44.8 %). Acceptance reads from the response `timings` object
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(`draft_n`, `draft_n_accepted`) — never on a synthetic repeat (greedy-text
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acceptance lies).
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## Vision contract
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`--mmproj` is the entire vision path (the GGUF carries no vision tensors).
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Probes: a solid-color PNG **≥ 256 px** answers its exact color — a tiny
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probe undersupplies image tokens and the model invents ("video"); the
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legacy top-level `images` field is IGNORED, only the OpenAI `image_url`
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content part reaches the model. Same traps the MiMo eras documented.
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## Measured: the 1 × 131,072 MTP boot (2026-10-05, historical)
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- **Boot ledger**: `creating MTP draft context against the target model
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'…/Swift-1.5-Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp.gguf'`, `loaded multimodal
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model, '…/Swift15-IQ3S/mmproj-Qwen3.8-27B-F16.gguf'`, `n_slots = 1,
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n_ctx_slot = 131072` — every expected line, no q8→f16 fallback.
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- **VRAM: 19,404 used / 4,721 MiB free** (nvidia-smi `free` field). The
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4.5 GiB prediction held; f16 KV would have left ~700 MiB, so this free
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number doubles as the q8_0 proof.
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- **Decode + MTP acceptance** (draft counts from the live `timings`):
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temp 0.8 → 66.1 tok/s, 182/349 accepted (52.1 %); temp 0 → 66.9 tok/s,
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166/318; **deployed recipe (temp 1.0/top_p 0.95/top_k 20) → 58.9 tok/s,
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159/355 (44.8 %)** — temperature buys fluency, costs acceptance and rate.
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For scale: MiMo Q6_K measured 94.4 tok/s on the same card — this 27B at
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IQ3_S runs ~2/3 the rate with ~3× the capability class.
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- **Vision**: 512×512 solid-red PNG → `Red`, `finish_reason: stop`.
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- **Template gate**: `reasoning_effort: xhigh` → 200 with
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`reasoning_content` populated; `high` → HTTP 500 (Jinja raise) — the
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models.yml fold is mandatory, exactly as the MiMo eras found.
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- Streaming completion: 200. No first-request silence window (the
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halogen-era 45–60 s stall has no analogue here).
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## Measured: the 2 × 131,072 no-spec boot (2026-10-06, live)
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- **Boot ledger**: `loaded multimodal model, '…/Swift15-IQ3S/
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mmproj-Qwen3.8-27B-F16.gguf'` and NO draft-context line (speculation
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off). `/slots`: **2 slots, n_ctx 131,072 each** (pool 262,144).
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- **VRAM: 22,728 used / 1,397 MiB free** (nvidia-smi `free` field) — the
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predicted 0.3–1.3 GiB window held; the old 2-3 GiB floor is knowingly
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violated by Frank's order. After a 512×512 image probe: 1,363 MiB —
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the vision transients fit.
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- **Decode without the drafter**: 48.0 tok/s (temp 0) / 47.8 (deployed
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recipe temp 1.0). `draft_n` absent from `timings` (no drafter). The MTP
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era's 58.9–66.9 tok/s is the honest price of the second context:
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−18–28 %.
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- **Vision**: 512×512 solid-red PNG → `Red` again on this shape.
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- Deploy: commit 812d9eb, e2e gate 33/33 green on the live fleet.
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## Client contract
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- Reasoning in `reasoning_content` (`--reasoning-format deepseek`); thinking
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tokens COUNT against `max_tokens`.
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- The embedded chat template gates `reasoning_effort` to
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`{xhigh, medium, low}` — anything else is a raise/HTTP 500, so
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`models.yml` `compat.reasoningEffortMap` folds the harness levels onto
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that set (mandatory, same as every Qwen3.8-template endpoint).
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- Sampling rides the wire (`extraBody`): Swift's publisher recipe temp 1.0
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/ top_p 0.95 / top_k 20 / min_p 0 (the card was evaluated at exactly
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this recipe at ctx 131,072).
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- Swift 1.5 is a reasoning-efficient post-train: −58.5 % median thinking
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tokens vs base at equal-or-better accuracy. Token budgets go further;
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the 32,768 `maxTokens` is unchanged from the MiMo era and still clears
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the compaction invariant (91,750 + 32,768 ≤ 131,072).
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- The GSQ-RCO "IQ3_S" tier is a **per-tensor allocation mix** (IQ2_XS 144 /
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IQ3_XXS 96 / Q6_K 78 / F32 360 / BF16 96 / Q3_K_M 39 …), all stock quant
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types — stock llama.cpp loads it. Publisher KLD vs Swift BF16: 0.0513
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(development), held-out 0.024–0.052 per domain; the MTP packaging is NOT
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separately evaluated by the publisher.
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## Rollback
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The 1 × 131,072 MTP shape is ONE commit away — revert 812d9eb (the
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two-slot order) and redeploy: the same env trio then ships
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`SPEC_TYPE=draft-mtp`, `UBATCH_SIZE=1024`, `CTX_SIZE=131072`,
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`PARALLEL=1` (the measured 58.9–66.9 tok/s with the head drafting).
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Two payloads on disk, both fetchable by the same script's git-history
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recipes:
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1. **MiMo-V2.6 Q6_K 2×200,704 f16 KV** — the payload that was LIVE until
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this cutover: `/home/dank/models/MiMo-Q6K/`; revert
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[[frank-small-llama-mimo-q6k-2x200704]] (env trio at commit e5893dc or
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380aafa's parent), one `MODEL_FILE` + shape edit.
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2. **Ornith-1.5-9B Q8_0** — the committed-but-never-deployed swap:
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`/home/dank/models/Ornith-Q8/`; revert to 380aafa's tree (ONE native
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262,144 slot, f16/f16 KV).
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## Trail
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- The Ornith-1.5-9B Q8_0 swap (77decb5 → 380aafa, earlier 2026-10-05) was
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committed and pushed but its deploy never completed (blocked at the
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whole-tree docs gate); the live service was still MiMo Q6_K when Swift
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cut over. Both Ornith payloads were verified on disk before Swift.
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- Swift header facts (block_count 65, interval 4, KV geometry, nextn) were
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read from the Hub file by HTTP range + struct parse — no download needed —
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before the payload was fetched.
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- Cutover 2026-10-05 ~23:26: the radiance-cutover session (parallel) label-
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committed both sets at Frank's direction — 1919ad7 (frank-primary radiance)
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then baf33d0 (this swap: trio, seam, runbooks, fleet docs). Deploy ran
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`deploy.sh dankclaw --service frank-small`; the service dispatch and health
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gate went green; the first e2e run failed ONE spec (12-crawl,
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`net::ERR_ABORTED` on `www.franksdank.cloud` — a transient, unrelated to
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frank-small), green on rerun.
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- The unit's `Description=` (MiMo era) was stale at cutover time and was
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updated in-repo afterward — the relinked unit picks it up at the next
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deploy/restart, not retroactively.
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- 2026-10-06 (Frank): drop MTP, skip ngram, ubatch 512, TWO 128k contexts
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(812d9eb). The tight fit landed: 1,397 MiB free, vision `Red`, decode
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48.0 t/s no-spec. Model of the trade: the drafter's ~0.4 GiB + ubatch
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~0.3 GiB bought the second 4,352 MiB KV slot.
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