Capacity trade: the 9B dense-hybrid (qwen35: 32 layers = 8 full-attention
+ 24 Gated DeltaNet, 4 KV heads x 256 dim, native 262,144, MTP-less,
natively multimodal) costs ~7 GiB of weights where the 26B MoE cost
~16.6 GiB. The freed room buys back the second conversation slot and
exact KV: --ctx-size 401408 --parallel 2 (two 200,704 windows), f16 K +
f16 V, MTP off (the file carries no nextn/mtp tensors - flag-only enable
is impossible), vision via the publisher's BF16 mmproj, ubatch 1024
(the CUDA decode-optimal value), verbosity 4, publisher sampler recipe
(0.6/0.95/20/0) in models.yml.
Hosts with the MiMo-V2.6-Distill Q6_K boots at this geometry: 21,276 MiB
used / 2,849 free at ubatch 1024, 40,960 tokens of fp16 KV at ubatch
2048. Compaction stays routed here; window math is unchanged (maxTokens
16,384 keeps the worst-case harness request inside the slot).
Gemma4 payload (Q4_K_M + mmproj + MTP assistant) stays on disk as the
rollback; its runbook is retired in place, keeping the attention_k_eq_v
pair-billing law.
Co-Authored-By: omp <omp@franksdank.cloud>
Verbosity 4 paid for itself: the engine's own llama_kv_cache lines give the
exact accounting — the cache bills the K+V pair TWICE under attention_k_eq_v
(6.125 B/elem at f16 K + q8_0 V), reproducing 3,001.25 MiB (5 full layers at
n_head_kv 2) + 306.25 MiB (25 SWA rings at n_head_kv 8, window 1024) to the
byte. The earlier "bill K-only" note was wrong; full layers have 2 KV heads,
not 8.
Deployed boot: 21,868 used / 2,257 free — the f16-K raise (+2,161 MiB KV) is
funded by the ubatch 2048 -> 1024 cut (~616 MiB of compute buffer) plus
variance, so exact K came essentially free. Measured decode 139.9 t/s temp 0;
vision probe returns Red at prompt_tokens 151.
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).
Frank's order the same night. The 1024->2048 rung measured +4.6 %
prefill for 616 MiB on the 3090 (2026-10-05 boot pair); the 112k cut
left 1,751 MiB free, so it rides with ~1.1 GiB predicted margin.
Decode is ubatch-invariant; batch 4096 >= 2048 keeps the seam happy.
Cross-cutting rename of the current llama.cpp endpoint on the RTX 3090
(port 7771) from frank-small to frank-secondary:
- Service trio: scripts/{frank-small.env,frank-small.service,
serve-frank-small.sh,download-frank-small.sh} → frank-secondary.*
- Test: tests/frank_small_unit.bats → tests/frank_secondary_unit.bats
- Runbooks: serverAppConfigs-docs/LLM/frank-small-*.md →
frank-secondary-*.md (9 files); the FreeToken runbook stays
freetoken-frank-small.md (it documents the retired CUDA-era service)
- Identifiers: FRANK_SMALL→FRANK_SECONDARY, llm_small→llm_secondary,
LLM_SMALL_*→LLM_SECONDARY_*, deploy_llm_small→deploy_llm_secondary
- Historical references to the OLD frank-small (FreeToken/CUDA on the
3090, and the Dankserver service that became frank-medium) are
preserved verbatim — they describe what the service was called
at the time.
Frankandomp