frank-small: reslice to 2 x 262,144 native slots (was 4 x 151,552)

The KV pool stays pinned at 606,208 tokens (card is full: 531 MiB free at
the old shape; autofit's 687,388 would leave 0.53 GB and OOM on the first
long request). 2 x 262,144 = 524,288 leaves ~82k tokens of pool slack.

Motivation: harness compaction. frank-primary's contextWindow 262,144
compacts at 70% = 183,501 tokens, and the compaction request carries a
32,768-token summary budget -> 216,269 must fit ONE frank-small request.
The 151,552 slot window could not hold it; the native window does.

No spec-decode interaction: checkpoint ships zero mtp.* tensors (config
lies), seam keeps every --speculative-* flag away from the engine.

AGENTS.md

@@ -26,7 +26,7 @@ merge absorbed the former `vllmScripts` repo, history preserved).
 |--------|---------|---------|-------|------|
 | Dankserver | `frank-primary` | tcclaviger RDNA4 vLLM fork (`docker.io/tcclaviger/vllm@sha256:da4029666…`, digest-pinned, plain `podman run`, root systemd unit) | `orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8` (~172.8 GiB, 131 shards), TP=2, expert offload automatic (fork plans it), prefetch OFF, **bf16 KV** (`--kv-cache-dtype auto`), **no speculative decode**, MNBT 2048, MoE gather 32×64, **2 seqs × 262144 ctx (the model's full native window)** at KV_BYTES 7,300,000,000/rank (bf16 measures 13,839 B/token), with **`--expert-precise-memory`** — the fitted 5.25 GiB overhead instead of the 7.60 GiB default, which hands the compile/graph-capture headroom to the expert arena (~7,278 slots vs 6,248) — util 0.98, and the client contract wired: `--reasoning-parser qwen3` (thinking in `reasoning`, never inline), `--enable-auto-tool-choice --tool-call-parser qwen3_xml`, default chat-template kwargs `enable_thinking` + `preserve_thinking`. Capacity history: five full-length contexts boot but leave ~0 bytes free at runtime (a real request with `max_tokens=261149` killed the worker: `Tried to allocate 50.00 MiB ... 0 bytes free`); six never fit (6×241664 asked 10.70 GiB vs 9.18 GiB free). DCP cannot help here — it requires TP > the model's 2 KV heads, i.e. four GPUs. fp8+MTP4 shape restorable from git tag `frank-primary-fp8-mtp-20261001` | 7770 |
 | Dankclaw | `frank-large` | gufo `gufo-org/gufo` v0.1.1, the Strix Halo engine, BUILT FROM SOURCE (root systemd unit; links the host ROCm 7.2.4) | Swift-1.5-Qwen3.8-27B-Uncensored UD-Q8_K_XL (27B dense, ABLITERATED/uncensored, 29.3 GiB, SWIFT OPEN LICENSE 1.0) with the z-lab DFlash2 Q4_K_M drafter (adaptive block policy, cap 7) on the gfx1151 iGPU (Strix Halo LPDDR, 114 GiB GTT), 262144 ctx single session, greedy, gufo's compiled-in Qwen renderer (NO Qwen-Sharp), text only | 7770 |
-| Dankclaw | `frank-small` | SGLang in a self-contained python3.12 venv (root systemd unit; the venv carries its own CUDA 13 stack — see the runbook) | letechlead MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound (qwen3_5 hybrid, 9B dense, 12.0 GiB, INT8 W8A16 AutoRound, in-checkpoint vision tower, NO MTP weights shipped so no spec decode) on the RTX 3090, fp8 KV, pinned 606,208-token pool / 4 slots of 151,552, bf16 mamba states, eager prefill, 83.9 tok/s decode | 7771 |
+| Dankclaw | `frank-small` | SGLang in a self-contained python3.12 venv (root systemd unit; the venv carries its own CUDA 13 stack — see the runbook) | letechlead MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound (qwen3_5 hybrid, 9B dense, 12.0 GiB, INT8 W8A16 AutoRound, in-checkpoint vision tower, NO MTP weights shipped so no spec decode) on the RTX 3090, fp8 KV, pinned 606,208-token pool / 2 slots of 262,144 (native window; 2026-10-01 reslice from 4 x 151,552 for compaction headroom), bf16 mamba states, eager prefill, 83.9 tok/s decode | 7771 |
 
 Retired endpoints (`frank-npu`, and every prior runtime) are in
 the [runbook index](#runbook-index). The full swap history lives in
@@ -414,10 +414,14 @@ dtype* (fp32 at 110 slots, bf16 at 217 — same 5.1 GB), so both dials are
 pinned: `--mamba-ssm-dtype bfloat16 --max-mamba-cache-size 32` (795 MiB).
 The KV pool is then **pinned at 606,208 tokens** (`--max-total-tokens`) —
 the engine's autofit picks 687,388 and leaves 0.53 GB, which Triton's
-deferred kernel loads eat and the first long request OOMs on. Four
-151,552-token slots; a single request may grow to the whole pool (170k
-verified). Prefill runs **eager** (`--disable-prefill-cuda-graph`) — there
-is no headroom for capture; decode graphs are on.
+deferred kernel loads eat and the first long request OOMs on. Two
+262,144-token slots at the model's NATIVE window (2026-10-01 reslice from
+4 x 151,552: 2 x 262,144 = 524,288 leaves ~82k tokens of pool slack, and
+a compaction request — frank-primary's trigger is 183,501 tokens plus a
+32,768-token summary budget = 216,269 — now fits ONE request); a single
+request may grow to the whole pool. Prefill runs **eager**
+(`--disable-prefill-cuda-graph`) — there is no headroom for capture;
+decode graphs are on.
 
 **No speculative decode — a checkpoint fact.** `text_config` declares
 `mtp_num_hidden_layers: 1`, but the shipped safetensors (base BF16 and this