serverAppConfigs/serverAppConfigs-docs/LLM/frank-primary-radiance-swift15-w4dn8.md

# frank-primary — Radiance (StillDeadcode), Swift1.5 Qwen3.8-Flash-Next W4Dn8, 2× R9700 TP=2

**Status: STAGED — activates at the cutover below.** · **Host:** Dankserver (192.168.0.235) · **Port:** 7770 · **GPU:** 2× Radeon AI PRO R9700 (gfx1201), TP=2

The FP8-native era (`qwen4exp-fp8-native.rad`, 173.0 GiB, no-recipe convert)
is replaced by a **GPTQ-calibrated 4-bit container** of
`ukisai/Swift1.5-Qwen3.8-Flash-Next` (BF16, 335.3 GiB, abliterated
finetune) converted with the recipe
`scripts/recipes/qwen4exp-swift15-w4dn8-i8-hc8m.recipe` on engine
**1.0.13** (`stilldeadcode/radiance@sha256:4c3f484564…` — same digest as
the FP8-native era; 1.2.0 was used ONLY for the calibration serve).
Same port, alias, container name, systemd unit. Rollback: revert the
`MODEL_FILE` line in `scripts/frank-primary.env` + redeploy —
`/home/dank/models/rad/qwen4exp-fp8-native.rad` stays on disk (trash
policy; 173 GiB, purge when the window closes).

## Why this swap

- **Context economics at production memory budgets**: the FP8-native
  experts (56.4 GiB/rank slice) forced a 40 GiB/rank pinned host pool and
  left KV ~3.5 GiB. W4Dn8 experts cut the resident set to ~1/4, freeing
  host and VRAM budget for KV and slots at equal-or-better measured
  decode (gate: ≥ 30.8 t/s vs the 30.08 t/s control).
- **Swift 1.5 base**: abliterated finetune of Flash-Next (Frank's
  fleet-personality call; frank-large serves the same family).
- **GPTQ closes the precision gap**: RTN alone on BF16 weights lands
  measurably worse; GPTQ with Hessians from a 10M-token corpus of this
  model's own distribution recovers most of it, verified end-to-end by a
  KLD gate against the BF16 container itself (KL ≤ 0.03, top-1 ≥ 95 %).

## The payload chain

1. **Fetch**: `scripts/download-frank-primary-swift15.sh` →
   `/home/dank/models/Swift1.5-Qwen3.8-Flash-Next` (131 shards, 335.3
   GiB, per-shard LFS sha256 verified, no token on the command line).
   48 layers, 512 experts (top-10 routed), moe_inter 640, hidden 2560,
   PLE 20M-vocab table 95.37 GiB, MTP head, vision tower.
2. **BF16 container**: `run-swift15-bf16.sh convert` →
   `rad-convert` no-recipe (pure copy) at `--max-ctx 4096` →
   `qwen4exp-swift15-bf16.rad` (335.28 GiB). Serves on 1.0.13 as the
   KLD reference engine (disk-tier placement; boot ~35 min).
3. **KLD reference**: `run-swift15-bf16.sh kld` (1.0.13) →
   `/home/dank/corpora/kld-ref` — `radiance-kld-1` format, `rows:
   50235`, 197 source-labelled docs, top-16 log-probs (f16), corpus
   fnv1a64 `a9d62b33c18b3d9c`. ~4 h at 32k prefill steps
   (`--max-num-batched-tokens 32768` — a 65536 step OOMs an arena
   tensor at `--max-model-len 16384`). **The wrapper's exit line is the
   receipt: never scp this script while it runs** (bash lazy-read;
   a mid-run swap killed a clean engine exit with rc=127, third fleet
   occurrence of the script-swap law). `kld-then-calib.sh SKIP_KLD=1`
   resumes from the `rows: 50235` receipt.
4. **Calibration**: `run-swift15-bf16.sh calib` on **1.2.0** (the only
   engine with `RADIANCE_CALIB_TOKENS`; grams are engine-invariant
   bf16 activations — RADGRAM2 format byte-identical across versions)
   + `calib-push.py` pushing `calib-corpus.jsonl` (10,014,932 tokens,
   1,294 prompts, assembled from real HF sources, chat-templated,
   source-labelled). The tap (in the `qwen4exp_fp8.so` architecture
   plugin) writes per-expert down-proj Gram matrices
   `gram.r<rank>.blk.L.ffn_down_exps.<e>.bin` (32-byte RADGRAM2 header +
   640×640 f32; `rows` = routing count, `trace` = activation energy)
   and stops the serve at the token threshold. TP=2: whole experts per
   rank (256/rank); gate_up input is rank-sliced (plugin warning — the
   recipe only casts the down projection).
5. **Protected-expert derivation**:
   `derive-protected-experts.py /home/dank/corpora/calib` → the 10
   highest-energy experts (5 per rank half) promoted to bf16. Protection
   law: energy share ≥ 3 % AND ≥ 3× routing share; even count per rank
   half; odd half gains the next most energetic.
   `apply-protected-cast.sh` splices the derived names between the
   `# PROTECTED-BEGIN/END` markers of the recipe (refuses double-derive).
6. **Final convert**: `convert-swift15-w4dn8.sh` (1.0.13, ~2 h, CPU-only)
   — gates: ≥48 gram files present, bf16 container already deleted
   (disk), ≥146 GiB free, output ≥126,000 MiB, `rad-info` shows the
   gptq receipt. No `--reuse`.

## The recipe tiers (scripts/recipes/qwen4exp-swift15-w4dn8-i8-hc8m.recipe)

| Tier | Encoding | Why |
|---|---|---|
| MoE experts `ffn_down` | **gptq w4n8 (W4Dn8)** | the campaign tier: GPTQ on Hessians from the 10M-token corpus |
| MoE `gate_up`, attention, shared expert | w4n8 | matched quantization; KLD-gated |
| 10 derived experts | **bf16 protected** | energy-share law (step 5) |
| trunk (embeddings, norms, conv) | **int8 (i8)** | trunk precision law |
| hyper-cond + MTP head | **fp8** | hc+mtp fp8 law |
| lm_head | **int8 (i8)** | i8 lm_head law |
| PLE n-gram table | fp8 at the checkpoint's fixed scale 1.9931793212890625e-04 | the fixed-scale law; absmax audit passed the 2⁻¹³..2⁻¹⁰ plateau |

## The shape (`scripts/frank-primary.env`)

Unchanged from the FP8-native era: TP=2 + `wht6`, `--max-num-seqs 3`,
`--max-model-len 200000`, MNBT 2048 (the MTP resonance law — 2560
collapses decode to 2.6–7.7 t/s), fp8 KV, `expert_tiered` host pool
40960 (the load-bearing floor), `--ngram-placement ram`, froggeric
v22.5 template override. `MODEL_FILE` points at
`/home/dank/models/rad/qwen4exp-swift15-w4dn8.rad`; the serve size floor
`FRANK_PRIMARY_RAD_MIN_MIB` moves 177000 → (real output size, set at
cutover from `rad-info`, MEASURED@cutover).

## Gates (measured at cutover)

- **KLD gate** (`kld-gate-swift15.sh`, candidate on 1.0.13 vs
  `kld-ref`): mean KL ≤ 0.03, top-1 ≥ 95 %. Fail → escalate gate_up
  w4→w5nl (pre-authorized), re-convert, re-gate.
- **Throughput gate**: decode ≥ 30.8 t/s at the 43.6k greedy probe
  (control: 1.0.13 + fp8-native drew 30.08 / accept 0.7549). Fail →
  fall back to the w4 down tier (Q35).
- MEASURED@cutover: decode t/s, acceptance, prefill, boot ledger, KV pool,
  KLD numbers.

## Deploy + verify

```bash
sudo systemctl stop frank-primary          # drained window
bash convert-swift15-w4dn8.sh              # if not already run
./scripts/deploy.sh dankserver --service frank-primary
```

Post-cutover checklist: unit active/enabled; `/health` 200; boot ledger
(expert pool coverage now w4-sized, KV pool should be larger than the
FP8-native era's 399,824 tokens); MTP draft counts in `timings`; froggeric
probe; ≥256 px `image_url` vision probe answers the color; tool-call
probe; `reasoning_effort` fold; Prometheus target green; `tests/run.sh`
+ Playwright e2e green.

## Rollback

| Layer | Path |
|---|---|
| FP8-native radiance (immediate) | revert `MODEL_FILE` in `scripts/frank-primary.env` + redeploy; `qwen4exp-fp8-native.rad` (173.0 GiB) on disk |
| FreeToken PR #587 | git tag `frank-primary-freetoken-pr587-20261005` |
| tcclaviger vLLM shape G | git tag `frank-primary-vllm-shapeG-20261003` |

Campaign artifacts on disk: BF16 checkpoint (335 GiB), `kld-ref` (24
GiB), grams (`/home/dank/corpora/calib`), corpora JSONL, logs
`/home/dank/logs/swift15_*.log`. The BF16 `.rad` container is deleted
before the final convert (disk gate) — the raw checkpoint is the
re-convert source if the window ever reopens.

## Links

- [[frank-primary-radiance-qwen38-native-fp8]] — the replaced FP8-native era
- [[LLM/index]] — fleet index
- [[swift15-campaign-worklog]] — campaign record
- [[Dual-R9700-Cooperation]] — the board swap that made TP=2 legal here