The serve script now passes --chat-template-file pointing at the
Qwen-Sharp v22.4.0 template. Without it the binary falls back to the
built-in peg-native template, which produces a ~73,600-token prompt for
a ~250-token request. With the sharp template wired in, the same request
produces a 62-175-token prompt.
Knowledge-base follow-up to a45f396. The runbook, both index one-liners, and
the AGENTS.md topology row all still declared FP8 active; flipped to
just1moremodel/Qwen3.8-27B-Uncensored-MXFP4-awq with unquantized bf16 KV (pool
486,464 tokens, full 262,144 window), and recorded the causal nuance: fp8 KV
was on both arms, so the FP8-vs-MXFP4 gap was weight precision, not KV - clean
KV is a quality hypothesis for W4A8, not a throughput one. No verdict yet.
The quadlet's "TEXT ONLY ... 400 here" comment was wrong: vision works on the
MXFP4 checkpoint (Qwen3_5ForConditionalGeneration carries the vision tower
through the Gemma4 merge path, unquantized) - verified by naming a solid red
48x48 PNG "Red". Comment corrected; harness models.yml input stays [text,image].
Docs-only; no re-deploy (the endpoint already serves vision).
The first cutover crash-looped the unit with 'invalid split file name':
the fetch script concatenated the three split parts into a single GGUF,
but part 1's header carries ggml.file_count=3, so the byte-correct
concatenation still advertises itself as a split and the loader demands
a -NNNNN-of-NNNNN filename.
- serve-frank-large.sh: -m points at part 1; llama.cpp loads the split
natively (parts 2-3 auto-discovered in the same directory)
- deploy-remote.sh: LLM_LARGE_MODEL gate path follows
- download-frank-large-unsloth.sh: assembly removed; the parts ARE the
canonical payload, verified against live Hub LFS oids
- docs: runbook model section + troubleshooting note, AGENTS.md, log
- the redundant 87 GiB assembled file is staged on dankclaw at
~/.AGENTTRASH/20260921-frank-large-assembled/
The verification looped over every LFS file under UD-IQ4_XS/ and MTP/ in
the live Hub tree — the five MTP head variants we do not fetch (BF16,
Q4_K_M, Q8_0, shared-BF16, shared-Q4_K_M) printed MISSING, set ok=False,
and set -e killed the script silently between verification and assembly
after a 3-hour download. Verify exactly the FILES set instead (passed to
python as argv), and report NOT IN HUB TREE when an expected file has
vanished upstream. Also fix the layout comment: the transport parts live
in UD-IQ4_XS/, not parts/.
New runbook frank-large-unsloth-qwen38-flash-next.md (runtime, payload,
deployed config, the explicit -md, the 114 GiB GTT memory model, client
contract, rollback). frank-large-ciru-orca.md marked RETIRED (rollback
target, payload and runtime intact on disk). AGENTS.md topology row,
frank-large section, harness note, runbook index, and the GPU-budget
lesson (GTT aperture ~114 GiB, not the stale 64 GiB rocm-smi figure —
the CIRU Orca held 92.6 GiB on the same device). LLM index header,
mermaid, active list, and the vault root index updated. Work-log entry.
Runbook deployed-flags table and AGENTS.md now name the template
(froggeric v22.4.0, repo-tracked, terse by default) and the rollback
target; the stale qwen-fixed-v22.3.jinja row and the long-gone
MM_MERGE_ENGINE note are gone.
DFlash2 (100.0 t/s decode, 287.1 t/s burst-4) beats MTP self-speculation
(85.9 t/s, 179.7 t/s) despite a lower accept length (4.24 vs 5.66): the
small separate drafter steps faster than the target's own MTP layer applied
autoregressively. DFlash2 is the deployed shape; both swap-script paths now
default to dflash/7. Docs updated.
- shared/prometheus/rules/llm-fleet.yml: the llamacpp reuse recording rule
divided cached by prompt, but llama.cpp's prompt_tokens_total EXCLUDES
cached tokens (its own HELP line), so the ratio was unbounded — measured
77 on a fully-warm frank-large, meaning LlmPrefixCacheCollapse could never
fire on that side. Now cached / (cached + prompt), with the traffic floor
counting both terms too; the header documents the unit trap. Also fixed the
LlmEndpointDown description: frank-large's CIRU llama.cpp build DOES export
the llamacpp:* family (verified live), so the alert covers all three
endpoints.
- shared/grafana/provisioning/dashboards/llm-fleet.json: re-cut for two
namespaces. Every panel reads both (the endpoint picker selects); the
KV-pool-fill panel retired 2026-09-16 returned with
vllm:kv_cache_usage_perc; the latency p95 panel returned with the vLLM
histograms (TTFT/ITL/e2e); the alerts panel is scoped to the fleet's
Llm.* rules; the stale halogen-era description is gone. All 21 panel
expressions validated against the live endpoints.
- runbook + log + Observability: prefix caching measured, not inferred —
reuse happens at 1,648-token block granularity (attention block size padded
to the mamba page size); an identical 13,021-token prompt went 2.30 s cold
to 0.68 s warm with 9,888 tokens (76 %) reused, while a 2,521-token prompt
registered zero hits. Rule counts corrected to 6 alerts + 3 recording rules.
./tests/run.sh: 325 pass.
The radiance TP=2 cutover changed the metric namespace frank-medium exports
(llamacpp:* -> vllm:*) and left two scrape targets addressing host processes
by an address a container cannot reach.
- shared/prometheus/rules/llm-fleet.yml: two namespaces side by side. Added
LlmRequestsWaiting, LlmKvCacheSaturated (vllm-only gauges llama.cpp never
had), the job:llm_vllm_prefix_cache_reuse:rate5m and
job:llm_spec_accept_length:rate5m recording rules, and re-cut
LlmPrefixCacheCollapse / LlmSpecDecodeOff to OR both families with
per-family traffic floors so an idle endpoint cannot fire them. Every
expression validated against live Prometheus.
- shared/prometheus/prometheus.yml: frank-small -> host.containers.internal:7771
and frank-large scraped at host.containers.internal:7770. Both are HOST
processes on Dankclaw and netavark DNATs published container ports only, so
the LAN-IP targets were red by construction; frank-large's CIRU llama.cpp
build does export the llamacpp:* family, contra the old comment.
- tests/observability_quadlet.bats: the two seams now encode the new contract
(per-endpoint reachability by process type; every named series must be on the
measured list for its engine; engine-independent rules must name both).
- homepage docs.html/services.json: frank-medium sees pictures, frank-large is
CIRU Orca with a single seat (was halogen w4b, two seats, 200k).
- docs: radiance runbook is ACTIVE (deployed flags, three-arm battery, verified
capabilities, rollback, replica-era sections labelled); llama.cpp runbook
carries the SUPERSEDED banner; Dual-R9700-Cooperation states the measured
verdict; Observability records the namespace split and the DNAT lesson;
AGENTS.md topology/frank-medium/Model Config/Benchmarking Policy/runbook
index flipped; both indexes updated; work-log entry added.
Also repaired agent-pass damage: prose prepended above frontmatter openers,
duplicated runbook bodies, a literal tool-call token pasted into a runbook, and
an index destroyed by diff artifacts (restored from HEAD, flips re-applied).
Vault link check: 128 pages, 0 unresolved. ./tests/run.sh: 325 pass.
Reanalysis after the 2026-09-20 swap to an ASUS ProArt B850-Creator WiFi
NEO: both R9700s now sit on CPU GPP root ports (x8/x8 Gen5 bifurcation),
every bridge reads AtomicOpsCap Routing+, and both endpoints read
AtomicOpsCtl ReqEn+ (CAP_EXP+28.w = 0x1440) — the exact precondition
Dual-R9700-Cooperation's test plan named. TP=2 is therefore unblocked,
not proven: no collective has been dispatched since the swap,
GGML_HIP_RCCL is still OFF, and the 272 t/s "tensor" number on record
measured a butterfly fallback.
- Dual-R9700-Cooperation: short answer rewritten, re-measured 2026-09-20
topology table, rebuild-hypothesis door marked moot, probe plan is now
standing work.
- Dankserver System Specs: Motherboard section; GPU BDFs 0b:00.0 ->
07:00.0, iGPU 10:00.0 -> 11:00.0, kernel 7.0.0-31, SMT on, and the new
eno2 (192.168.0.247) second 5GbE port holding the low-metric default
route while eno1 keeps the fleet's static .235.
- frank-medium-llamacpp-dflash2: rationale and hardware row split past
from present; dated work-log sections stay as history.
- AGENTS.md + both indexes: no longer assert a wall that no longer exists.
Docs only; frank-medium stayed active and healthy throughout (verified
/health). ./tests/run.sh 331/331.
The frank-medium runbook's deployed-flags table still carried the
predecessor's values (35,30 / 393216 / 196608 / draft-mtp / BF16 mmproj);
updated to the deployed shape (32,33 / 327680 / 163840 / draft-dflash / f16
mmproj) from scripts/frank-medium.env. The halogen runbook still described
itself as 'the active frank-large runbook'; marked RETIRED 2026-09-19 with a
pointer to [[frank-large-ciru-orca]].
The vLLM detour (a2b39b1, same day) is retired: the Q4_K_M llama.cpp setup
is the requested shape and the vLLM KV-quant options on sm_86 all measured
dead (fp8 hardware-impossible, int8 page-size unification, turboquant
mm-prefix). Root unit restored, vLLM quadlet/Dockerfile/fetch script moved
to .AGENTTRASH, runbook listed as same-day-reverted. Rollback target:
frank-small-vllm-gemma4.
Runtime swap on the RTX 3090 (port 7771):
- vLLM gemma-x86_64-cu129 dev build, digest-pinned, audio extra pip-installed
into localhost/vllm/vllm-openai:frank-small (Dockerfile, no COPY lines)
- google/gemma-4-12B-it-qat-w4a16-ct (10.26 GiB int4) + Google's bf16 MTP
assistant (845 MB) — the w4a16-ct assistant cannot draft in vLLM (drafter
path skips Marlin; acceptance 1.00), bf16 measures 2.80-3.56
- root systemd unit -> rootless Quadlet (dankclaw/frank-small/quadlet/);
manual CUDA device+lib mounts (no nvidia-container-toolkit on host)
- bf16 KV (fp8 hardware-dead on sm_86), 289,647-token pool, 2 concurrent
full-context sessions, CUDA graphs on
- native text+image+audio: the fleet's multimodal endpoint
- measured: pp@67k 1293 t/s, pp@213k 608 t/s, tg@213k ~13.6 t/s,
tg@85k ~17.6 t/s
- host driver 610.57.04 (Ubuntu 26.04); sm_86 is correct, no arch override
- planner/scoping: frank-small now selected by dankclaw/frank-small/ +
env/serve/download trio; old unit retired to scripts/.AGENTTRASH/
- docs: new runbook frank-small-vllm-gemma4.md; AGENTS.md, LLM index,
top docs index updated; old runbook moved to retired
--cache-ram caps the total bytes of saved prompt states in HOST RAM, and
alloc() refuses any single state larger than the whole cap. That refusal was
firing in production: 137 times in the two days from 2026-09-16, at 11.0-11.4
GiB per state, so every conversation past ~170k tokens was uncacheable and
re-prefilled from scratch on its next turn.
The state law at this shape is 68 KiB/token (16 full-attention layers x 4 kv
heads x 256 dim x 2 B x 2 for K/V, plus the MTP draft context's 4096 B), so
8192 MiB held ~120k tokens and 16384 holds ~240k: a FULL 196608-token slot
state (~12.8 GiB) now fits with ~3 GiB spare.
Host RAM only, allocated on demand and never pinned, so the VRAM fit is
untouched. New seam: the cap must clear one full slot's state and stay under
half the host's RAM (it fails on the old 8192 and passes on 16384). Also
corrects the adjacent claim that 0 is the build's default for
--ctx-checkpoints -- this binary's --help says 32.
The two R9700s sit on unequal PCIe paths: ROCm0 (03:00.0) is CPU-root-port
Gen4 x16 (~31.5 GB/s); ROCm1 (0b:00.0) rides the B650 chipset through
bridges negotiating Gen4 x1 (~1.97 GB/s). With the MTP drafter, output
layers and heavier compute buffers pinned to the last-layers card, live
rocm-smi read 98% busy on the x1 card vs 40% on the x16 card. Moving one
DeltaNet layer (34) to ROCm0 shifts ~0.43 GiB off the bottlenecked card;
the seam fit lands 30.59/30.01 with gap 0.58 GiB, inside floor and slack.
36:29 fails both gates, so this lever is spent.
- runbook: identity now 4x262144, audio verified, throughput table with
the OOM and negative-result rows, deployed flags updated to reality.
- AGENTS.md frank-small paragraph matches the deployed shape.
- log.md: the sweep entry.
- scripts/frank-small.env: my earlier line-range edit had clobbered
NGL=999 and FLASH_ATTN=on out of the file; the seams caught it. The
live service was unaffected because the script's defaults match the
declared values exactly, but the file contract is restored.
Suite: ALL TESTS PASSED (321), vault 125 pages 0 unresolved.
The 393216/34:31/MTP deploy measured 30.78 GiB on ROCm1 against the
fit's 28.32 — the MTP draft buffers (one nextn layer's KV, 4096 B/pos,
plus draft buffers) came in 2.46 GiB above the estimate. Recalibrate
the seam's MTP constant to the measured 4.20 GiB total charge on card
1 and drop the floor 1.5 -> 1.0 GiB for this shape (ROCm1's 1.08 GiB
headroom is real; 35:30/36:29 fail card 0's floor at this pool, so
34:31 is the only split that fits 2x196k).
AGENTS.md and the runbook move to the MTP drafter: 34:31, 393216 pool
(196608 per conversation), the DFlash2 sidecar documented as a
one-line revert, and a dated part-2 section with the fit/measured
table and the recalibration.
AGENTS.md topology, Active Services, the CUDA-quant-KV lesson (f16 is no
longer why), and the runbook index. New frank-small-gemma4-12b runbook:
payload digests, the SWA/q8 arithmetic behind --fit's 262k window, the
MTP-sidecar + ngram-mod chain, the always-accepted reasoning_effort, and
the fit-probe error that looks like a fault at boot. The Qwen runbook and
both indexes carry the retirement; work log updated.
AGENTS.md topology row and section, and the runbook: the pool is 327680
positions (163840 per conversation over two slots), the split is 36:29 -- one
layer past the 34:31 balance at this context, on purpose, for headroom on the
drafter card (fit 29.19/26.04, measured 28.40/26.66 GiB at load, 3.46/5.20
headroom) -- and vision is on via the explicit --mmproj flag, because this
build has no autoload (the first deploy came up text-only and 500'd image
requests). The rope caveat is written down where the cap lives: the GGUF has
no scaling keys, so the top 65k of the pool extrapolates on the base rope.
6.44 / 6.90 is the state straight after load; after the service has served
traffic it sits at 6.23 / 6.64, with and without requests in flight. Both are
~5 GiB above the floor, but the runbook should not imply a load-dependent
difference that the two readings do not actually show.
New page [[frank-medium-batch-ubatch]]: the sweep's method (one invocation per
cell, a VRAM sampler per cell, 64k prefill measured AT 64k depth), the full
batch x ubatch matrix, the depth-0 control, the deployed-shape VRAM table, and
the limitations — including the one that cost me two runs, that amdgpu does not
return ~26 GiB at once, so a reload after a kill fails with "unable to allocate
ROCm0 buffer" and reads exactly like a configuration that does not fit.
AGENTS.md: the batch lesson now carries the measured curve (the peak at 512, the
10 % loss at 2048, the irrelevant logical batch, the invariant decode) instead
of the "~3.3 vs ~1.7 GiB" figure, which was measured at the bench's shape; at
the deployed shape the asymmetry is 2.41 against 1.30. Fleet row and the
frank-medium section now say 35:30 and batch 6144x512.
Runbook: deployed flags, the split history with the ubatch-512 table, the fault
note, and the verified VRAM (6.44 / 6.90 idle, 6.23 / 6.64 under two concurrent
requests).
Dual-R9700-Cooperation: the live capability table (card 0 ReqEn+ against card 1
ReqEn-, x1 effective link on card 1) and an honest label on the M.2_2 riser
premise — it is ASUS's spec sheet, not a measurement, and CPU-attached does not
imply Routing+ on this board (00:08.3 is CPU-side and Routing-).
log.md: the round trip recorded, newest first.
The batch/ubatch sweep (scripts/bench-batch-ubatch.sh, 23 cells of a 28-cell
grid, 3 reps each) says the ubatch knob has an OPTIMUM, not a plateau:
ubatch 256 384 512 768 1024 1280 1536 1792 2048
tok/s 1046 1068 1193 1135 1152 1151 1165 1148 1078
The curve is remarkably reproducible -- 512 came out 1192.88 / 1193.23 /
1193.28 / 1193.88 across batch 2048, 4096, 6144 and 8192, and 2048 came out
1077.38 / 1077.54 / 1077.59 -- so this is a deterministic property of the
shape, not noise. The logical batch is throughput-neutral (2048..8192 all
within 2 % at a fixed ubatch) and VRAM-neutral (the compute buffers are sized
by ubatch alone). Decode is 15.88 tok/s at depth 65536 on every single cell.
So the deployed 6144x1536 was both 2.4 % slower than the optimum and 3.71 GiB
more expensive. Measured at the deployed shape (262144, 2 slots, DFlash2):
36,29 ubatch 1536 -> 4.71 / 4.91 GiB free (what was deployed)
36,29 ubatch 512 -> 6.01 / 7.32 GiB free (ubatch alone)
35,30 ubatch 512 -> 6.44 / 6.90 GiB free <- deployed
The ubatch move freed 1.30 GiB on ROCm0 but 2.41 GiB on ROCm1, because ROCm1
holds the output layers and the drafter's graphs -- so it shifted the balance
toward ROCm1 by 1.31 GiB and the split had to follow it one layer. 0.46 GiB is
one DeltaNet layer's worth of asymmetry, i.e. the granularity floor: no split
can be tuned finer than a layer, which is why 34,31 is not better.
Re-fitted the seam with both ubatch coefficients measured at this shape and
re-anchored it on the new deployed point (it reproduces 6.44 / 6.90 to
0.01 GiB). Every neighbouring split still fails it: 36,29 -> 1.85, 34,31 ->
0.94, 37,28 -> 3.24, 1,1 -> 3.03, 39,26 -> 6.03 GiB.
Also replaced the unit test's literal `TENSOR_SPLIT=36,29` assertion with the
shape it actually cares about -- two shares that add up to the model's 65
blocks, with ROCm1 taking the fewer -- so re-measuring the balance no longer
breaks a test about parallelism. The numeric contract lives in the seam test.
pcie-link-test.cu (CUDA, pinned buffers, cudaEvent timing, both services stopped):
pinned H2D 6.72 GB/s and D2H 6.60 GB/s, i.e. 85 % of the Gen4 x4 ceiling. Async
is no better than sync and pageable sits within 1 % of pinned, so these copies are
link-limited rather than staging-limited — the usual "pageable costs 2x" does not
apply on this host. A 3 MiB slab costs 474 us, essentially 3 MiB / 6.72 GB/s plus
~27 us of launch.
That settles the expert-streaming question quantitatively: 1.70 GiB of active
experts per token (A3B @ Q4_K_M, 75 GiB expert mass) is 272 ms of link time ⇒
3.7 tok/s, 4.6 with a fifth of the experts resident. The same bytes computed in
host RAM at 256 GB/s cost 7.1 ms — the link is 31x slower than the memory behind
it, which is why llama.cpp's -ot exps=CPU path measured 20.46 tok/s while an
engine that streams loses by 3-5x. The port under the card is x8-capable and the
card is x16-capable, so the x4 is the adapter; doubling it still leaves streaming
well behind.
Also records FreeToken's own constraint: it keeps experts in host RAM with an LRU
GPU cache (exactly this streaming shape) and loads only modelopt block-FP8
safetensors for qwen3_5_moe, so Q4_K_M GGUF is unloadable there regardless.
The harness is in the repo now, so the runbook says how to run it and what the
tool will not tell you:
- / splits devices within one configuration and , splits sweep values, so a
legitimate --tensor-split 36,29 would have benched one card at a time.
- there is no -c: n_ctx = n_prompt + n_gen + n_depth, so no bench can decide
whether a configuration's buffers fit beside the deployed 262144 KV.
- a test that cannot allocate exit(1)s the process, hence one invocation per
cell.
- a shell's memlock limit (8 MiB here) is not the unit's (infinity), which
fails the load for the wrong reason.
- no --spec-* and no --parallel: decode figures are drafterless and slots are
never exercised; -d is what puts KV in front of the measurement at all.
Operator instruction: purge the cache so no run can serve a stale payload. The two
live payloads were cleared and then re-fetched rather than left absent — deleting
them without a re-fetch means neither endpoint starts.
halogen's re-fetch proved the point: its sidecars had been stale *in place*
(overlay.hgn 2,477,677,120 -> 2,572,466,560 bytes, overlay-speed.hgn
2,383,306,048 -> 2,478,095,488) while the 115.55 GiB checkpoint returned
byte-identical. frank-small's 27B and mmproj re-fetched to Hub-matching hashes,
unchanged.
Trap recorded: podman refuses a bind mount whose source directory is missing
(statfs ... no such file or directory), so frank-large needs /models to exist
*empty* for its first-start fetch to run.
Q4_K_S against the recorded Q4_K_M numbers: +2.1/+1.6/+2.6 % (iGPU-only pp512 /
pp16384 / tg64), +2.7 % tg32@64k, +4.1 %/+2.0 % for the two layer-split configs,
~0 on both pp512@64k, host RAM bottoming at 10.0 GiB against ~5 GiB. A memory
lever with a small speed dividend. IQ4_XS (97,473,155,360 bytes, sha256
b4787265...d0574f9d) is pulled and verified for the next comparison.
Also repairs an AGENTS.md edit that landed in the wrong section: the peer
session's commits shifted that file between my read and my write, so the
frank-large text briefly split the Model Config section.
The note described DSpark as the deployed drafter and 40:25 as the split; both
were true for a few hours. It now leads with DFlash2 at 36:29 and keeps the
excursion as the record it is:
- the drafter comparison table with DSpark's REAL size (1,455,376,576, not the
1,359,284,737 that went into the fetch script), and why it lost: no sliding
window, so its draft KV spanned the whole context.
- the split's two moves as one story: the batch pushed it to 40:25, the drafter
swap pulled it back to 36:29, with both measurement tables.
- the layer-size law (0.43 GiB DeltaNet, 1.43 GiB attention) as the reason the
balance is measured and not interpolated.
- the verified-behaviour section now carries the LIVE numbers: 4.71 / 4.91 GiB
free (4.43 / 4.61 under load, 0.18 GiB gap), the DFlash2 init lines, and
draft acceptance from both slots (0.63 / 0.48 on slot 1, 0.39 on slot 0).
- the fault note scopes its own evidence: 39:26 was loaded, not exercised.
The note still described DFlash2, one slot at 262144 and a 1:1 split -- all of
which the day's work replaced. It now carries:
- the DSpark swap with the table that matters (1.27 vs 1.92 GiB, block_size 7 vs
8 so n_max 6 vs 7, a Markov head instead of the candidate selector, and NO
sliding window) and the rule behind the sizing: the draft context is built
with n_ctx = llama_n_ctx(ctx_tgt), so a drafter without a window caches the
whole target context -- 5.0 GiB here, against DFlash2's ~40 MiB.
- the failure that rule produces when ignored: load succeeds, /health answers,
and the first draft decode dies with an OOM at 1:1.
- why the split moved a second time: tripling the batch costs ROCm1 about twice
what it costs ROCm0, with the 38,27 -> 41,24 -> 40,25 measurement table.
- the deployed flags, the 2-slot shape (n_slots = 2, n_ctx_slot = 131072), the
DSpark init lines, and balanced 29.98 / 29.98 GiB cards.
- honest scoping on the older measurements: the throughput, drafter-worth and
ngram tables were taken on DFlash2, and the agent-loop numbers on one slot.
- the 39:26 page-fault signature as a thing to watch, marked as NOT an OOM.
Correcting a claim I made from a bad query: Q4_K_S does exist for this finetune.
`mradermacher/Qwen3.8-Flash-Next-Uncensored-i1-GGUF` ships the large quants as
`.partNofM` fragments — Q4_K_M 37.00+37.00+36.97 = 110.97 GiB (which is how the
deployed file was assembled) and Q4_K_S 35.00+35.00+34.09 = 104.09 GiB — while
the smaller rungs are single files. A tree listing filtered on `.gguf` makes
Q4_K_S invisible, which is exactly how I concluded it did not exist.
Also records the fetch trap that hid it for a moment: `curl -o FILE URL` exits 0
on 401/403, so a gated repo produced three 153-byte "shards" with identical
sha256 values and a cheerful DOWNLOAD_DONE in 20 s for 104 GiB. -f plus the
Hub's declared size plus the LFS sha256 is the standard the fleet's own
download-frank-medium-gguf.sh already meets.
The log mtimes plus each run's own duration pin it: the first 'invalid internal
status' in the user journal is 18:58:30, while the F bench (launched 18:54:31)
was still loading, and the preceding llama-cli placement probe had just spilled
3.2 GB of '> ' prompts. The note had said 'after the experiment'; that was wrong
and is now recorded with the timestamp it can be checked against.
I had written 'memory pressure from the 116 GiB iGPU runs' as the cause of the
pause-process death. journalctl -k records no OOM kill for that window and the
kernel says nothing else about it, so the claim was a guess wearing a finding's
clothes — in AGENTS.md, the x4 note, and the log. All three now state the
trigger is not established, and the note's 'co-tenants' patience' bullet no
longer asserts that causality either. AGENTS.md also gains the real lesson:
journalctl -k is the check, and an unknown cause does not need a story.
The ledger number in the note was pre-reboot. Same model, same pool, no clamp —
but the host was measurably more fragmented when it came back, which is the sort
of thing that decides whether the next co-tenant fits.
Asked whether Vulkan on both devices unlocks the split. It does not: the
per-tensor design aborts byte-identically, because the gate is not the driver
mix but `--override-tensor` — `has_tensor_overrides()` is a required term of
the scheduler's `pipeline_parallel` flag (llama-context.cpp:433, the only place
in the tree that reads it), and that flag sets `n_copies` in
`ggml_backend_sched_new`. With `n_copies == 1` a pre-allocated weight on a
non-primary device has no backend and the graph aborts.
Chasing it exposed a harness artifact that invalidated the earlier conclusion:
llama-bench splits a device LIST with `/` and SWEEP values with `,`, so
`-dev CUDA0,Vulkan1` was two single-device runs all along (and `-ts 0.85,0.15`
two sweep values, i.e. device 0 takes everything — which is where the bogus OOM
came from). With the correct syntax two-device splits work in both flavours:
pure Vulkan -dev Vulkan1/Vulkan0 -ts 0.85/0.15 -> 27.55 tok/s @64k (12.8 GiB on the 3090)
cross-vendor -dev CUDA0/Vulkan1 -ts 0.15/0.85 -> 27.23 tok/s @64k, pp512 268.5 (15.0 GiB)
iGPU alone 25.77 tok/s @64k, pp512 231.8
+7 % decode, +16 % prefill — real but not a regime change, and it costs the
3090 ~15 GiB, which this fleet spends on its only vision endpoint. The design's
premise still fails: whole layers carry their experts (1.62 GiB each), the 12
attention layers are spread every 4th, and the 32.8 GiB PLE must stay on the
main device, so KV cannot be consolidated on the 3090.
Also records the evening's incident (a dead rootless podman pause process took
all container management down; `podman system migrate` panics in 5.7.0; reboot
repaired it) and the netavark host-address lesson from the hermes 502.
The design we sketched (trunk + KV on the 3090, MoE experts on the iGPU) is not
expressible in mainline llama.cpp. Per-tensor cross-backend placement aborts in
the scheduler -- "pre-allocated tensor (blk.0.ffn_down_exps.weight) in a buffer
(Vulkan1) that cannot run the operation (NONE)" -- and both per-layer
cross-backend forms fail at load. CUDA + Vulkan cannot serve one model; the CPU
is the only fallback side that works, which is exactly why -ot exps=CPU runs.
What the same build does instead is the surprise: iGPU-only (Vulkan/RADV, PLE in
page cache) gives 32.64 tok/s shallow, 25.77 tok/s at 64k depth and 456.7 tok/s
prefill, with the 3090 idle at 0 %. That matches halogen's deployed ~25 tok/s --
but commits 116 of the host's 121 GiB against halogen's 95.4 held with 14.7
spare, so it is not deployable beside the co-tenants. Throughput parity, memory
bankruptcy: the fleet's two-endpoint split stands, now on evidence rather than
preference.
New page LLM/x4-pair-experiment.md carries the tensor inventory, the results
table, the two scheduler limits, reproduction commands, and the traps found on
the way. Both index pages also stop calling halogen retired -- the ik swap's
stale claims were still sitting in them.
ngram-mod is draftless (added to the spec config vector unconditionally, while
every model-backed drafter needs ctx_dft), so unlike MTP it can share the
process with DFlash2. Chained at the fleet's 48/64 window, over three shapes:
prose 1k/512 dflash 43.77 | ngram 17.72 (0 drafts) | chain 43.65
echo 1.5k/400 dflash 76.82 | ngram 102.50 | chain 200.58
structured/400 dflash 91.08 | ngram 17.80 (0 drafts) | chain 91.22
identity dflash 70.37 | ngram 17.77 | chain 70.40
On prose the chain is byte-identical to the drafter alone (same 119 drafts/49
accepts) -- that is what makes it a safe default -- and on prompt-echo traffic
it is 2.6x. VRAM is unchanged: the matcher is a 64 MiB host-RAM hash table.
The window sweep says keep the long one: 48/64 beats 16/32 (161.0) and 8/16
(113.8) on echo, and shortening it costs prose (43.9 -> 36.0) because the
matcher then proposes on ordinary fragments and the rejections still have to be
verified. That is the 'ngram hurts' result this fleet hit twice before.
Two documentation traps recorded with it: ngram-mod prints NO startup banner in
this build (its drafts are only visible behaviourally), and the harness's
'structured' shape is a negative control because its lines differ.
Four configurations of the same binary, identical prompts at temperature 0, the
unit stopped between runs, on the deployed payload:
none 17.7 tok/s card1 26.07 GB
draft-mtp n=3 32.4 tok/s 58 % accepted card1 29.35 GB
draft-mtp n=7 26.7 tok/s 33 % accepted card1 29.65 GB
draft-dflash 7 43.5 tok/s 41 % accepted card1 29.42 GB
DFlash2 is worth 2.46x over autoregressive and 34 % over the best MTP, and all
four produced IDENTICAL greedy text, so the 'lossless verification' claim in the
runbook is now a check rather than an assumption. MTP is not the cheaper option
either: its head loads ~3.3 GB against the drafter's 2.06 GB file, and deeper
drafting loses (n=7 accepts a third of its proposals, n=3 more than half).
The two CANNOT be chained, and the failure is structural rather than tunable:
'spec-type draft-mtp,draft-dflash' dies at load with 'context type MTP requested
but model doesn't contain MTP layers', because a chain has ONE draft context and
MTP builds against whatever model that context holds -- here the DFlash2 file.
The serve script therefore passes --spec-draft-model in the dflash branch ONLY,
and the seam now asserts exactly that (the wiring whose violation is this
error), plus that the deployment stays on the measured winner.
scripts/bench-spec-ab.py makes the comparison reproducible: the benchmarking
policy wants the runtime's own harness for this, and the numbers above were
otherwise unreproducible one-offs.
The loader prints no per-device ledger at this verbosity, so the claim is
measured rather than read: +131072 tokens of context added 4.83 GB to one card
and 4.84 GB to the other (both carry their own attention layers' KV), and
neither card's total usage could hold the 31.46 GB file. Worth writing down
because the retired shape WAS two full copies — that is what a replica is, and
it is why the 29.8 GB FP8 checkpoint could never run there.
The LLM index still opened with vllm-radiance as frank-medium's runtime and
drew the replica pair in its topology diagram; the cooperation page's thesis
(collectives are impossible, so the answer is hardware) now has to name the
path the fleet actually took: llama.cpp's layer split, which launches no RCCL
kernel on either card. That reframes the M.2 riser as a means to TENSOR
parallelism rather than a means to using both cards at all.
Two families of ~30k-token turns ran against the deployed endpoint: 24.8 s and
51.4 s for the first turn (the second waits for the slot), 30.7 s and 8.0 s for
the second. Against the prefill table that is ~25 s of cold prefill plus the
wait, so the honest reading is that ONE slot is now the limiting resource for
concurrent agent loops — the trade this deployment makes for giving a single
conversation the whole 262144-token window. --parallel splits the window; it
does not add throughput.
The harness header still described the retired two-replica proxy ('the deployed
routing pins such a conversation to one replica', vLLM's prefix-cache key). It
now says what is true: one endpoint, one slot, concurrent families queue, and
the old routing numbers are history in the runbook.
Context: 262144 was measured before it was deployed -- 24.72 GB on GPU 0 and
29.14 GB on GPU 1 of 34.21 GB each, ~5 GB of headroom on the busier card, and a
140,069-token prompt prefilled through the single slot in 134 s to prove the
window is real. The 114688 wall was the vLLM predecessor's arithmetic, not this
runtime's.
Throughput, measured through the service: 1.0-1.4k tok/s prefill from 4k to
140k, 43.8 tok/s decode on a 512-token generation, 41-71 % DFlash2 acceptance,
and the prefix cache re-prefilling 4 of 998 tokens on a repeated prompt.
The signals move with the runtime, so the fleet's rules and dashboard are
re-cut rather than renamed: vllm: series do not exist any more, and two of the
old rules watched things llama.cpp does not export at all (KV-pool fill, p95
latency). Those are retired with the reason written down, and LlmSpecDecodeOff
takes one of the slots -- a lost drafter is the failure no client can see. The
observability seam now fails if any rule names a series the endpoint does not
export, which is what would have caught the stale vllm: expressions.
omp models.yml (outside the repo) is updated in the same pass: contextWindow
262144, and the full reasoning-effort map, because Qwen3.8's template answers
500 on 'high' -- verified against the live endpoint, low/medium/xhigh answer
200. Subagents run at high.
The runbook for the new deployment, plus the sweep of everything that still
described the vllm-radiance replica pair: the vault index and its ACTIVE
marker, the superseded banner on the radiance page, the pointer from the
ROCmFPX page, the homepage card, the Grafana dashboard description and the
observability page's scrape table.
The new page carries the two facts a future agent needs and the flags do not
say: llama.cpp's layer split is what lets BOTH cards serve ONE model without
any collective (vLLM's PP handoff is an RCCL send/recv, which is the primitive
this host cannot dispatch), and the rocBLAS Tensile-path trap that makes a
healthy-looking build fail on the first request.
halogen-flash-server is ACTIVE again with its 2026-09-16 measured ledger (budget
33.5 GiB against a need of 27.2 — no clamp — and 14.7 GiB left for everything
else), ik_llama.cpp is retired with its measurements kept as the record of why,
and the new frank-small runbook covers the -mtp file, the 64 KiB/token KV
arithmetic, the MTP contract, and the reasoning_effort trap that cost me every
subagent on the endpoint.
AGENTS.md: topology, Active Services, runbook index, and three new llama.cpp
lessons (MTP is a property of the file; --jinja is what `tools` needs; a model's
template can reject the harness's thinking level). Three pre-existing defects
found while editing it: a truncated sentence mid-file, a harness path that does
not exist on either server, and the benchmarking stop/mask recipe still calling
frank-large a root unit.
Truthfulness notes worth keeping: the co-tenant stall NOTE prints again, so the
claim that it "no longer prints" is gone and the three observed block counts are
recorded instead of a guessed threshold; and the Observability page says out
loud why frank-large has no scrape job rather than leaving a silent absence.
FrankandClaude