Frank
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Payload: HauhauCS/Gemma4-26B-A4B-QAT-Uncensored Q4_K_M (16,796,015,520 B) + the publisher's BF16 mmproj, /home/dank/models/Gemma4-26B-A4B/. Shape: ONE 200,704-token slot (--parallel 1; 2x200,704 does not fit the 24 GiB card), f16 K + q8_0 V under flash attention, batch 4096 / ubatch 1024, --log-verbosity 4, MTP OFF (the gemma4-assistant file is on disk, not loaded: its draft KV is built against the target's full window, measured +1.9 GiB -> 23,806/319 free, no margin beside the f16-K raise). Measured boots (nvidia-smi): q8_0 K + q8_0 V / ubatch 2048 / MTP off = 21,890 used / 2,235 free; with the MTP assistant = 23,806 / 319. Engine facts recorded: gemma4 hybrid attention (25 sliding-window + 5 full-attention layers) so KV scales with 5 layers only, and attention_k_eq_v is honoured by build 5fc4f3c (pool bills K-only; the measured q8_0 pool = 2.05 GiB = the K-only figure). Serve script gained VERBOSITY (+ --log-verbosity in the argv), the SPEC_DRAFT_FILE drafter path, and defaults/lore retargeted to Gemma4. deploy-remote.sh payload gates follow the env. The frank-secondary bats seam is rewritten for the new contract (argv-based) and fixes a pre-existing vacuity: serve_argv regenerates the test env, so mutations made before it were silently undone - tests that mutate now exec through run_stage. frank-secondary is the fleet compaction hub (200,704 is the only window that fits a worst-case compaction input).
93 lines
4.4 KiB
Markdown
93 lines
4.4 KiB
Markdown
# frank-secondary — llama.cpp CUDA, Gemma4-26B-A4B Q4_K_M, 1×200,704 (Dankclaw)
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**ACTIVE since 2026-10-07.** RTX 3090, port 7771, root systemd unit
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`frank-secondary.service`, served by `scripts/serve-frank-secondary.sh` +
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`scripts/frank-secondary.env`. Supersedes
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[[frank-secondary-llama-swift15-unc-iq3xxs-mtp-114688]] (Swift-1.5-Qwen3.8-27B
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RCO-IQ3_XXS-mtp, 2×114,688, in-file MTP).
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## Payload
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|File|Path|Bytes|
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|---|---|---|
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|Main (Q4_K_M)|`/home/dank/models/Gemma4-26B-A4B/Gemma4-26B-A4B-QAT-Uncensored-HauhauCS-Balanced-Q4_K_M.gguf`|16,780,192,888|
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|Vision (mmproj BF16)|`/home/dank/models/Gemma4-26B-A4B/mmproj-Gemma4-26B-A4B-QAT-Uncensored-HauhauCS-Balanced-BF16.gguf`|~1.195 GiB|
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|MTP assistant (on disk, NOT loaded)|`/home/dank/models/Gemma4-26B-A4B/mtp-gemma-4-26B-A4B-it.gguf`|~0.252 GiB|
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Repo: `HauhauCS/Gemma4-26B-A4B-QAT-Uncensored-HauhauCS-Balanced-MTP`
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(base `google/gemma-4-26B-A4B-it`). Downloaded 2026-10-07 by plain
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`curl -fL` (no token needed, ungated).
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## Shape
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```
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--ctx-size 200704 --parallel 1 # ONE conversation, Frank's 200k cap
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--flash-attn on
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--cache-type-k f16 --cache-type-v q8_0 # exact K, FP8-class V (q8_0)
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--batch-size 4096 --ubatch-size 1024
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--n-gpu-layers 99
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--log-verbosity 4 # debug: KV layout, buffers, graph capture
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--spec-type none # MTP OFF (see below)
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--mmproj <BF16 projector>
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--jinja --reasoning auto --reasoning-format deepseek
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```
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Measured boot at **q8_0 K + q8_0 V, ubatch 2048, MTP off** (2026-10-07
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morning): **21,890 MiB used / 2,235 MiB free** (`nvidia-smi`). With MTP ON
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(the assistant loaded) the same shape was **23,806 / 319** — the drafter's
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context costs ~1.9 GiB because its KV is built against the target's full
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window ([[Llama Cpp Serving Sizing]]).
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Same evening (Frank): **K raised to f16, ubatch cut 2048 → 1024, verbosity
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4**. f16 K doubles the K side (20.5 KiB/token over the 5 full layers ≈ 4.1
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GiB at 200,704, +2.05 GiB over q8_0); the ubatch cut claws back part of it
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(the Swift-era 3090 measurement put the 2048 rung at ~746 MiB of compute
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buffers). Projected usage ~23 GiB — **the boot ledger is the referee, not
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this arithmetic**: on a 24,125 MiB card a failed graph capture is the failure
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mode. Decode is ubatch-invariant (Swift-era 3090 law; unmeasured on Gemma4 —
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inference).
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## Architecture facts
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Gemma4 MoE hybrid: 30 layers, 128 experts (8 active), n_embd 2816, 262,144
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native window, n_vocab 262,144. Hybrid attention: **25 sliding-window layers
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(window 1024) + 5 full-attention layers (5, 11, 17, 23, 29)** — the KV pool
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scales with the 5 full layers only (8 KV heads × 256 dim): q8_0 ≈ 10.6
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KiB/token, f16 ≈ 20.5 KiB/token. A 200,704 slot therefore costs ~2.05 GiB at
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q8_0 — far less than the Swift 16-layer shape (34 KiB/token).
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`attention_k_eq_v: True` — in `gemma4.cpp` the absent `wv` tensor makes
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`Vcur = Kcur` in the compute graph, and in this build (5fc4f3c) the KV cache
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**honours it: no V slots are allocated**. Measured: the q8_0 pool landed at
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~2.05 GiB, exactly the K-only figure. **Bill K-only.** The `--cache-type-v`
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flag is kept explicit for contract visibility; with `k_eq_v` it is inert.
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The llama.cpp master build at commit `5fc4f3c` supports the arch
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(`src/models/gemma4.cpp`, `LLM_ARCH_GEMMA4 = "gemma4"`). Note: `grep -c`
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arch names on the packed binary returns 0 for EVERY arch (including the
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`qwen3_5` it serves) — check the source tree, not the binary.
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## MTP law
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MTP for Gemma4 is a SEPARATE file (`mtp-gemma-4-26B-A4B-it.gguf`, arch
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`gemma4-assistant`), loaded via `--spec-draft-model` beside
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`--spec-type draft-mtp` — unlike Swift, whose MTP head ships inside the main
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GGUF. The serve script gained `SPEC_DRAFT_FILE` for this. 2026-10-07 (Frank):
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**MTP disabled** — `SPEC_TYPE=none` strips both spec flags (flags move as a
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set). The assistant payload stays on disk; setting `SPEC_TYPE=draft-mtp` +
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`SPEC_DRAFT_FILE` re-enables it at the cost of ~1.9 GiB (boots at 319 MiB
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free).
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## Verification
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- `curl http://192.168.0.143:7771/health` → `{"status":"ok"}`
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- `/v1/models` reports `n_ctx: 200704`, `ftype: Q4_K - Medium`
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- Vision probe: solid-color PNG ≥ 256 px via OpenAI `image_url` part,
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expect the exact color word.
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## Rollback
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Revert to the Swift trio: `MODEL_FILE=/home/dank/models/Swift15-UncIQ3XXS/…`,
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`CTX_SIZE=229376`, `PARALLEL=2`, in-file `SPEC_TYPE=draft-mtp` — the Swift
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payload remains on disk. See
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[[frank-secondary-llama-swift15-unc-iq3xxs-mtp-114688]].
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