frank-primary: roll back to qwen FP8 + MTP4 (2339fae trio)

DFlash2 experiment declared failed 2026-10-01: the drafter serves and
drafts (12.8 tok/s proposed) but acceptance is pinned at 1.0-1.38 on ALL
text classes including verbatim repetition — the aux-hidden-state capture
semantics are wrong (single-stream entering-state vs post-layer/comb is
the untested alternative). At ~1.2 acceptance the 8-token verify tax makes
decode 5x SLOWER than the 9.9-10.0 baseline (1.6-1.8 tok/s measured).

Restores the verified 37-40 tok/s shape: qwen3.8-flash-next FP8, MTP4,
prefetch off, 200k x 3 seqs, fp8 KV.
This commit is contained in:
Frank
2026-09-30 20:13:23 -07:00
parent caee26e3c3
commit d91379cff2
5 changed files with 88 additions and 199 deletions
+15 -23
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@@ -1,24 +1,17 @@
#!/usr/bin/env bash
# Payload inventory/verification for frank-primary:
# Intel/GLM-5.3-Flash-W4A16-AutoRound (AutoRound symmetric int4, group 128,
# packing "auto_round:auto_gptq": 34 numbered shards + model_extra_conv /
# model_extra_tensors, weight-map index, 113,074 tensors, ~170 GiB) — the
# int4 payload that became frank-primary on 2026-09-30.
# orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8 (compressed-tensors FP8, 131
# shards + weight-map index, ~172.8 GiB) — the tcclaviger-stack payload that
# became frank-primary on 2026-09-29.
#
# bash scripts/download-frank-primary.sh --verify-only (the default)
# bash scripts/download-frank-primary.sh --verify-only (the ONLY mode)
# bash scripts/download-frank-primary.sh --fetch
#
# THIS REPO IS PUBLIC (measured 2026-09-30: the payload fetched anonymously at
# bring-up). The LFS oids are still not verified byte-exactly here — the tree
# API masks them — so integrity rests on the weight-map index, the shard count
# and the loader's own tensor-shape checks at boot.
#
# WHY THIS QUANT: its quantization_config.quant_method is "auto-round", which
# the fork overrides to "inc" — that is the ONLY route to R4dW4a16MoEMethod
# (libr4d's grouped W4A16 GEMM) and therefore to an expert-offload recipe. A
# compressed-tensors W4A16 checkpoint of the same model (e.g.
# dealignai/...-CYBERSECURITY-W4A16) reaches TritonWNA16Experts instead, which
# has no offload recipe, and refuses to serve at all on this host.
# THIS REPO IS GATED (401 anonymous — measured 2026-09-29): anonymous fetch
# is impossible and the tree API masks LFS hashes, so a byte-exact upstream
# manifest cannot be built without the authed endpoint. The payload on
# /home/dank/models was fetched with the operator's HF token (out of band:
# HF_TOKEN in the environment, never in argv) at bring-up time.
#
# Modes:
# --fetch resume any missing/truncated shard via `hf download` with
@@ -31,17 +24,16 @@
# (slow, ~10 min for 173 GiB).
set -euo pipefail
REPO="Intel/GLM-5.3-Flash-W4A16-AutoRound"
DEST="/home/dank/models/GLM-5.3-Flash-W4A16-AutoRound"
EXPECTED_SHARDS=34
REPO="orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8"
DEST="/home/dank/models/Qwen3.8-Flash-Next-Uncensored-FP8"
EXPECTED_SHARDS=131
mode="verify"
[[ "${1:-}" == "--fetch" ]] && mode="fetch"
if [[ "$mode" == "fetch" ]]; then
# The repo is public, so no token is required; if one is present it is taken
# from the environment and never from argv (a -H header is readable in
# /proc/<pid>/cmdline — the 2026-09-16 leak).
: "${HF_TOKEN:?--fetch needs HF_TOKEN in the environment (never argv)}"
export HF_TOKEN
mkdir -p "$DEST"
hf download "$REPO" --local-dir "$DEST"
fi
@@ -89,7 +81,7 @@ if [[ "${2:-}" == "--hash" || "${VERIFY_HASH:-0}" == "1" ]]; then
echo "hashing every shard (slow)..."
cd "$DEST"
sha256sum -c --quiet model.safetensors.index.json 2>/dev/null || \
sha256sum model-*-of-00034.safetensors > /dev/null # presence check; content hash list printed on demand
sha256sum model-*-of-00131.safetensors > /dev/null # presence check; content hash list printed on demand
fi
[[ "$fail" -eq 0 ]] || exit 1
+37 -87
View File
@@ -1,53 +1,34 @@
# frank-primary.env — tcclaviger RDNA4 vLLM production config (dankserver :7770).
#
# 2026-09-30 cutover from orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8 (MTP4) to
# Intel/GLM-5.3-Flash-W4A16-AutoRound, the first payload this fleet has served
# through the fork's W4A16 expert-offload path. ROLLBACK: the pre-cutover qwen
# state is commit 2339fae ("frank-primary: fix the SIGPIPE race in both
# image-digest gates") — restore scripts/ from it and deploy; the qwen payload
# (173 GiB) and the R9V state dirs are untouched on disk.
# 2026-09-29 cutover from the R9V radiance-vLLM fork (its launcher/shim/state
# machinery is retired; /home/dank/r9v-state/{q8xl,uncensored} stay on disk as
# the rollback target, and git tag frank-primary-r9v-q8-20260929 is the last
# pre-cutover commit). The engine is the tcclaviger RDNA4 vLLM fork — the same
# digest-pinned image the 2026-09-29 tuning campaign measured — serving
# orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8 (~172.8 GiB, 131 shards) with
# the MTP4 drafter on the two R9700s.
#
# QUALIFIED 2026-09-30 by boot probe + bench against the live engine:
# * THE 35 tok/s TARGET IS NOT MET: decode 9.9-10.0 tok/s, prefill 918 tok/s
# (warm, 2.6k-token prompt) at 131,072 ctx x 2 seqs. See the runbook's
# "Why 35 tok/s is out of reach on this hardware" — the bound is the fork's
# expert-gather read path (8.2 GB/s effective vs the link's 22.74 GB/s),
# the same structural gap the 2026-09-29 qwen campaign measured.
# * Arena 14.51 GiB = 2,383 slots x 6.234 MiB per rank; 12,096 host-backed
# experts per rank, 73.64 GiB pinned. Live per-layer telemetry
# (R4D_LRU_TELEMETRY=1, 2026-09-30): hit rate 0.53-0.66, ~500-730 installs
# vs ~2,000 routed per layer over the window.
# * --expert-precise-memory is ON: it replaces the 6.25 GiB default
# compile-headroom figure with the registry's fitted 5.46 GiB, buying
# 1.43 GiB of cache (13.08 -> 14.51 GiB). Decode measured flat across that
# change (10.03 -> 9.88 tok/s), which is the evidence that the hit rate
# saturates near 0.6 and residency is no longer the binding term.
# * KV dtype stays bf16/AUTO — fp8 KV is NOT legal on this model. It disables
# _use_rocm_sparse_triton() in the ROCM_AITER_MLA_SPARSE backend (the
# predicate requires a non-fp8 cache), and that rope-free Triton path is the
# only MLA decode available on gfx12: aiter's MLA decode op is registered
# under @if_aiter_supported, i.e. gated on CDNA>2. With fp8 KV the MTP draft
# step dies with "'_OpNamespace' 'vllm' object has no attribute
# 'rocm_aiter_mla_decode_fwd'".
# * MTP4 spec decode is ABSENT DELIBERATELY, unlike the qwen shape. It WORKS
# here (the MTP head loads, architecture resolves to Glm5NextMTPModel, and
# acceptance is excellent: mean accepted length 3.76-4.90, per-position
# 0.92/0.85/0.69/0.58, 69-97%) — but it buys nothing on an offload-bound
# deployment: measured decode 9.6-11.2 tok/s (vs 10.0 without) while prefill
# COLLAPSED 918 -> 255 tok/s. The verification forward gathers the union of
# the batch's experts, so spec decode does not amortize a residency-bound
# gather the way it amortizes compute. It also costs 2.6 GiB of arena.
# Reinstate only with a fresh A/B on a non-offload-bound shape.
# * PREFETCH IS ABSENT BY LAW, unchanged from the qwen campaign: expert-cache
# telemetry measured the prefetcher at 36% precision and deleting the flag
# bought +40-51% decode. Never re-add --expert-prefetch without a fresh A/B.
# Every number here was QUALIFIED by boot probe on 2026-09-29 (not inherited):
# * MAXLEN 200000 x SEQS 3 (600k total) at KV q8/q8 fits with headroom:
# the engine measured "GPU KV cache size: 729,545 tokens; Maximum
# concurrency for 200,000 tokens per request: 3.65x" at KV_BYTES 7.2 GiB
# per rank. KV_BYTES is PER RANK — sizing it to the global requirement
# OOMs the worker (measured twice: 16 GiB and 9 GiB both die with ~7.5 GiB
# free; 7.2 GiB boots).
# * --kv-cache-dtype fp8 is the fleet's q8/q8 KV ask (e4m3 for BOTH K and V
# — the stock flag quantizes them together, which is exactly what was
# requested here). Accepted by the attention path; qualified with a
# completion probe.
# * PREFETCH IS ABSENT BY LAW: expert-cache telemetry measured the
# prefetcher at 36% precision (36,720 slabs prefetched, 13,369 served) —
# roughly half the gather traffic was waste; prefetch off is the tuned
# incumbent and the +40-51% decode came from deleting the flag. Never
# re-add --expert-prefetch without a fresh A/B.
# * TunableOp stays OFF: CLAV_TUNABLEOP_SWEEP silently skips under expert
# offload unless CLAV_TUNABLEOP_WITH_OFFLOAD=1, and forcing it corrupts
# numerics (repetition loops, early halts, invalid measurements).
# * KV is NOT capped explicitly: the fork's plan reserve (1.76 GiB at 131,072)
# already covers what max_model_len needs for this shape. It does NOT for an
# MTP shape — see the runbook's fork-bug section and
# scripts/patches/gpu_worker-kv-cap.patch.
# Decode at the tuned shape: 40.57/37.44/37.57 tok/s (166/1087/4064 ctx) at
# the 32k window; 42.94/34.55/36.09 at this 200k shape (arena 6,032 slots).
#
# HIP reads bare env vars TEMP, HOST, GPU_MAX_HEAP_SIZE — every key here is
# prefixed FRANK_PRIMARY_ so none can leak.
@@ -55,57 +36,26 @@
# --- runtime ----------------------------------------------------------------
# Digest-pinned: the floating :latest tag moved once already. Local alias
# qwen-fp8-runtime:tuned-20260929 (image ID 3322dbbbc96d) points at the same
# bytes in rootless storage. Same image as the qwen cutover — the W4A16 path
# (INC scheme -> R4dW4a16MoEMethod, libr4d grouped W4A16 GEMM) ships in it.
# bytes in rootless storage.
FRANK_PRIMARY_IMAGE=docker.io/tcclaviger/vllm@sha256:da4029666668b90a0386c1ed23ea370c79916ad4e1a6ad1dd9db098b9fa069ea
# --- payload ----------------------------------------------------------------
# Intel AutoRound W4A16: symmetric int4, group 128, packing "auto_round:auto_gptq".
# quantization_config.quant_method is "auto-round", which the fork overrides to
# "inc" (inc.py:364) — that is what routes the MoE to R4dW4a16MoEMethod instead
# of the compressed-tensors path's Triton experts, which has no offload recipe.
# 34 numbered shards + model_extra_{conv,tensors}.safetensors, 113,074 tensors.
FRANK_PRIMARY_MODEL_DIR=/home/dank/models/GLM-5.3-Flash-W4A16-AutoRound
FRANK_PRIMARY_MODEL_SHARDS=34
FRANK_PRIMARY_MODEL_DIR=/home/dank/models/Qwen3.8-Flash-Next-Uncensored-FP8
FRANK_PRIMARY_MODEL_SHARDS=131
# --- identity ---------------------------------------------------------------
# The harness models.yml id stays frank-primary (provider 192.168.0.235:7770).
FRANK_PRIMARY_CONTAINER=frank-primary-glm
FRANK_PRIMARY_CONTAINER=frank-primary-qwen
FRANK_PRIMARY_SERVED_NAME=frank-primary
FRANK_PRIMARY_PUBLISH=7770:7770
# Containers removed before every start: the pre-cutover qwen identity (it holds
# the same port and GPUs), the retired R9V identity, and the ad hoc experiment
# identity.
FRANK_PRIMARY_LEGACY_CONTAINERS="frank-primary-qwen frank-primary-r9v qwen-fp8 glm-probe"
# Containers removed before every start: the retired R9V identity and the ad
# hoc experiment identity (both hold the GPUs / name registrations).
FRANK_PRIMARY_LEGACY_CONTAINERS="frank-primary-r9v qwen-fp8"
# --- qualified engine shape ---------------------------------------------------
# 131,072 x 2 seqs. The window is NOT chosen for capacity: the engine's own
# plan reserve is one max_model_len request, and below ~92k tokens the fork's
# reserve model (13,600 B/token + a small mamba term) falls short of what the
# engine actually needs for this model's per-sequence KDA state, which makes the
# boot refuse ("2.07 GiB needed vs 1.74 GiB available"). 131,072 clears it with
# the plan's own cap intact. KV cache as built: 138,561 tokens, 1.06x
# concurrency for a 131,072-token request.
FRANK_PRIMARY_MAXLEN=131072
FRANK_PRIMARY_SEQS=2
# 0.99 fails boot ("Free memory on device cuda:1 ..."); 0.98 leaves the
# compile/capture headroom the plan models.
FRANK_PRIMARY_MAXLEN=200000
FRANK_PRIMARY_SEQS=3
FRANK_PRIMARY_KV_BYTES=7730934784
FRANK_PRIMARY_KV_DTYPE=fp8
FRANK_PRIMARY_SPEC=4
FRANK_PRIMARY_UTIL=0.98
# Prefill chunk. 2,048 is the qualified value; the expert union a chunk routes
# to saturates quickly, so the chunk size is an install-amortization knob, not a
# residency one. Measured 2026-09-30: NBATCH 8,192 boots (arena 12.51 GiB) and
# leads to the SAME warm prefill (922 vs 918 tok/s) — no reason to pay its
# 2 GiB of profile buffer.
FRANK_PRIMARY_NBATCH=2048
# GLM's own tool-call dialect. Without --enable-auto-tool-choice the endpoint
# rejects tool_choice "auto" outright ("\"auto\" tool choice requires
# --enable-auto-tool-choice and --tool-call-parser to be set"), which breaks
# every tool-using agent on the endpoint. Verified 2026-09-30: a get_weather
# prompt returns tool_calls with finish_reason "tool_calls".
FRANK_PRIMARY_TOOLPARSER=glm47
# GLM's reasoning dialect. Without it the model's thinking leaks into `content`
# (measured: content began with the answer, then "Let me verify: ... = 391"
# followed by a bare "</think") and the reasoning field comes back empty. With
# it, the chain of thought lands in `reasoning` — the vLLM field name the fleet
# documents (llama.cpp endpoints use reasoning_content).
FRANK_PRIMARY_REASONINGPARSER=glm47
+14 -12
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@@ -1,24 +1,26 @@
# frank-primary.service — tcclaviger RDNA4 vLLM endpoint
# (Intel/GLM-5.3-Flash-W4A16-AutoRound int4, 131,072 x 2 seqs, bf16 KV, TP=2,
# expert offload to pinned host RAM, 34-shard payload) on the 2x R9700 pair,
# dankserver :7770. 2026-09-30 cutover from orcarouter
# Qwen3.8-Flash-Next-Uncensored-FP8 + MTP4; commit 2339fae is the pre-cutover
# state and the rollback.
# frank-primary.service — tcclaviger RDNA4 vLLM endpoint (orcarouter
# Qwen3.8-Flash-Next-Uncensored-FP8, MTP4 spec decode, KV q8/q8, 600k total
# context over 3 sessions, TP=2, tiered experts, 131-shard payload) on the
# 2x R9700 pair, dankserver :7770. 2026-09-29 cutover from the R9V radiance
# fork (git tag frank-primary-r9v-q8-20260929 is the pre-cutover state; its
# launcher/shim/setup-state machinery is retired and the state dirs stay on
# disk as rollback).
#
# Same port, same served alias; the harness models.yml id is unchanged.
# The serve script drives `podman run` directly (the image entrypoint execs
# `vllm serve`) and then waits on the container, so a crashed engine is a
# nonzero ExecStart and Restart=on-failure is real.
#
# WHY A ROOT UNIT (not a rootless quadlet): the expert-offload shape pins
# 73.64 GiB per rank of host RAM (the expert host rows). Pinned pages are charged against RLIMIT_MEMLOCK; dank's
# WHY A ROOT UNIT (not a rootless quadlet): the tiered-expert shape pins tens
# of GiB of host RAM (the expert host slabs, ~20.5 GiB per rank of pinned
# anonymous memory). Pinned pages are charged against RLIMIT_MEMLOCK; dank's
# login session on this host carries 8 MiB and a user quadlet is capped by the
# user manager's own hard limit — raising that means restarting
# user@1000.service and bouncing every user container on the host. A root unit
# grants LimitMEMLOCK=infinity to the dank process via PID1, and the image
# stays in dank's rootless podman storage.
[Unit]
Description=frank-primary — tcclaviger vLLM GLM-5.3-Flash int4 W4A16 on 2x R9700
Description=frank-primary — tcclaviger vLLM Qwen3.8-Flash-Next-Uncensored-FP8 on 2x R9700
After=network-online.target
Wants=network-online.target
@@ -33,9 +35,9 @@ Environment="FRANK_PRIMARY_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-pr
ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-primary.sh
# systemd stop: wait alone cannot stop the container child; stop it
# explicitly. vLLM 0.26 drains gracefully on SIGTERM.
ExecStop=/usr/bin/podman stop -t 120 frank-primary-glm
# Boot cost: int4 payload page-in plus torch compile/graph capture —
# ~7 min measured 2026-09-30 on a warm page cache, longer cold.
ExecStop=/usr/bin/podman stop -t 120 frank-primary-qwen
# Boot cost: FP8 payload page-in plus torch compile/graph capture —
# ~15 min cold (measured 2026-09-29), faster warm.
TimeoutStartSec=1800
Restart=on-failure
RestartSec=10
@@ -1,37 +0,0 @@
--- a/vllm/v1/core/kv_cache_utils.py
+++ b/vllm/v1/core/kv_cache_utils.py
@@ -1395,10 +1395,34 @@
return kv_cache_spec
max_page_size = max(page_sizes)
+ # GLM-5.3-Flash + a draft model: the sparse indexer k_cache page is
+ # tokens_per_state x the MLA page (same per-token bytes), and MLA layers
+ # cannot be PADDED to an arbitrary page size (sparse MLA indexes the cache
+ # in whole token rows) -- but they CAN grow their block size when the max
+ # page is an exact multiple of the MLA page. Bump the max page to a
+ # multiple of every MLA-family page so all of them take the divisible
+ # block-growth branch below instead of the padding refusal, while the
+ # draft and mamba layers simply pad to the (slightly larger) page.
+ mla_pages = {
+ spec.page_size_bytes
+ for spec in kv_cache_spec.values()
+ if isinstance(spec, MLAAttentionSpec)
+ }
+ if mla_pages:
+ mla_common = math.lcm(*mla_pages)
+ max_page_size = -(-max_page_size // mla_common) * mla_common
new_kv_cache_spec = {}
for layer_name, layer_spec in kv_cache_spec.items():
if layer_spec.page_size_bytes == max_page_size:
new_kv_cache_spec[layer_name] = layer_spec
+ elif isinstance(layer_spec, KpoolTailSpec):
+ # The kpool tail kernel pins the tail block to the kpool size
+ # (tail_kv_cache.view(...) must be [blocks, 2, index_kpool,
+ # head_dim]); growing block_size breaks that contract. Pad the
+ # physical page instead -- the tail is its own group and the pad
+ # wastes bytes only.
+ new_spec = replace(layer_spec, page_size_padded=max_page_size)
+ new_kv_cache_spec[layer_name] = new_spec
elif isinstance(layer_spec, MambaSpec):
# MambaSpec's page size is determined by its state shapes and does
# not scale with block_size, so pad the page instead. This is the
+22 -40
View File
@@ -1,30 +1,27 @@
#!/usr/bin/env bash
# serve-frank-primary.sh — frank-primary endpoint (tcclaviger RDNA4 vLLM fork,
# Intel/GLM-5.3-Flash-W4A16-AutoRound, 2x R9700, dankserver :7770).
#
# 2026-09-30 cutover from orcarouter Qwen3.8-Flash-Next-Uncensored-FP8 + MTP4.
# Rollback: commit 2339fae carries the whole pre-cutover scripts/ tree; restore
# it and deploy. The qwen payload and the R9V state dirs stay on disk.
# orcarouter Qwen3.8-Flash-Next-Uncensored-FP8 + MTP4 spec decode, 2x R9700,
# dankserver :7770; 2026-09-29 cutover from the R9V radiance fork — git tag
# frank-primary-r9v-q8-20260929 is the pre-cutover state).
#
# The engine is driven by `podman run` DIRECTLY: the image's entrypoint execs
# `vllm serve "$@"`, so the run line below IS the engine argv.
# `vllm serve "$@"`, so the run line below IS the engine argv. This replaces
# the R9V launcher/shim machinery (that fork needed a docker->podman shim and
# a 104-key on-host setup state; this stack is fully expressed by flags, and
# every flag here was qualified by boot probe on 2026-09-29 — see
# frank-primary.env for the qualification record).
#
# Why this payload runs the offload path at all: 170 GiB of int4 experts cannot
# fit in 64 GiB of VRAM, so the engine keeps 12,096 experts per rank in pinned
# host memory and serves them through a 2,383-slot VRAM LRU arena. The MoE
# kernel is libr4d's grouped W4A16 GEMM (R4dW4a16MoEMethod), reached because the
# checkpoint's quant_method "auto-round" is overridden to "inc" by the fork.
#
# Shape: MAXLEN 131,072 x 2 seqs, bf16 KV, util 0.98, MTP OFF, prefetch OFF.
# Measured 2026-09-30: decode 9.9-10.0 tok/s, prefill 918 tok/s warm. The
# 35 tok/s target is NOT met — the bound is the fork's expert-gather read path
# (8.2 GB/s effective vs the link's 22.74 GB/s); see frank-primary.env and the
# runbook's arithmetic section.
# Shape: MAXLEN 200000 x 3 sessions (600k total), KV q8/q8 (--kv-cache-dtype
# fp8: e4m3 for both K and V — the stock flag quantizes them together, which
# is the requested q8/q8), KV_BYTES 7.2 GiB PER RANK (the engine measured
# 729,545 tokens of capacity / 3.65x concurrency at 200k per request), MTP
# depth 4, prefix caching, expert prefetch OFF (telemetry measured it at 36%
# precision — the tuned incumbent deletes it), TunableOp off.
#
# The root unit (scripts/frank-primary.service, User=dank,
# LimitMEMLOCK=infinity) grants the pin budget for the 73.64 GiB/rank of pinned
# host expert rows. A plain shell session also works, but the unit is the
# fleet-parity boot-persistent shape.
# LimitMEMLOCK=infinity) grants the pin budget for the tiered-expert host
# slabs (~20.5 GiB/rank of pinned anonymous memory). A plain shell session
# also works, but the unit is the fleet-parity boot-persistent shape.
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
@@ -47,9 +44,8 @@ set +a
: "${FRANK_PRIMARY_PUBLISH:?FRANK_PRIMARY_PUBLISH must be host:container}"
: "${FRANK_PRIMARY_MAXLEN:?FRANK_PRIMARY_MAXLEN must be set}"
: "${FRANK_PRIMARY_SEQS:?FRANK_PRIMARY_SEQS must be set}"
: "${FRANK_PRIMARY_NBATCH:?FRANK_PRIMARY_NBATCH must be set}"
: "${FRANK_PRIMARY_TOOLPARSER:?FRANK_PRIMARY_TOOLPARSER must be set}"
: "${FRANK_PRIMARY_REASONINGPARSER:?FRANK_PRIMARY_REASONINGPARSER must be set}"
: "${FRANK_PRIMARY_KV_BYTES:?FRANK_PRIMARY_KV_BYTES must be set (PER RANK)}"
: "${FRANK_PRIMARY_KV_DTYPE:?FRANK_PRIMARY_KV_DTYPE must be set (fp8 = q8/q8 KV)}"
# Capture podman's output BEFORE grepping: under `set -o pipefail`, the
# classic `podman images | grep -q` pattern races — grep exits on its first
# match, podman dies SIGPIPE (141) writing the remaining lines, and pipefail
@@ -104,34 +100,20 @@ podman run -d --name "$FRANK_PRIMARY_CONTAINER" \
--cap-add SYS_PTRACE \
--device /dev/kfd --device /dev/dri --device /dev/mem \
-e HIP_VISIBLE_DEVICES=0,1 -e VLLM_ROCM_USE_AITER=0 \
-e PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True \
-v "$FRANK_PRIMARY_MODEL_DIR":/models:ro \
"$FRANK_PRIMARY_IMAGE" /models \
--served-model-name "$FRANK_PRIMARY_SERVED_NAME" --port 7770 \
--tensor-parallel-size 2 \
--max-model-len "$FRANK_PRIMARY_MAXLEN" \
--max-num-seqs "$FRANK_PRIMARY_SEQS" \
--max-num-batched-tokens "$FRANK_PRIMARY_NBATCH" \
--gpu-memory-utilization "$FRANK_PRIMARY_UTIL" \
--enable-expert-offload \
--expert-precise-memory \
--kv-cache-memory-bytes "$FRANK_PRIMARY_KV_BYTES" \
--kv-cache-dtype "$FRANK_PRIMARY_KV_DTYPE" \
--enable-prefix-caching \
--enable-auto-tool-choice \
--tool-call-parser "$FRANK_PRIMARY_TOOLPARSER" \
--reasoning-parser "$FRANK_PRIMARY_REASONINGPARSER" \
--speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":$FRANK_PRIMARY_SPEC}" \
--trust-remote-code \
> "$LOG" 2>&1
# NOT passed, deliberately (each measured on this payload — see the env file):
# --kv-cache-dtype fp8 disables the sparse MLA backend's rope-free
# Triton path, which is the only MLA decode on
# gfx12 (aiter's MLA op is gated on CDNA>2).
# --speculative-config MTP head loads and accepts well, but buys zero
# decode and collapses prefill on an
# offload-bound shape.
# --expert-prefetch* 36% precision; deleting it bought +40-51%.
# --kv-cache-memory-bytes the plan's own reserve covers this shape.
# From here on, this script's lifetime IS the container's: wait returns the
# container's exit code, so a crash is a nonzero ExecStart and the unit's
# Restart=on-failure is real. (systemd stop goes through ExecStop in the