[Sync] Lua Hyprland chain, licence cleanup

fl/.config/llamacpp/config.ini

@@ -379,6 +379,36 @@ sleep-idle-seconds = 60
 #     stall/500) → any trial is a separate TEXT-ONLY preset; this one keeps MTP + vision.
 #     Open on Vulkan for MTP and DFlash alike: #28158 — intermittent draft token id 248320
 #     (= n_vocab) → HTTP 500 "Invalid input batch", mostly after very long prompts. If seen: that.
+#   ✦ 2026-10-22 QUANT RACE OPENED (reddit tip: ByteShape / ISTA 3-bit quants + DFlash2 + KV streaming):
+#     two bench-only candidate sections follow this preset — [Qwen3.8-27B-GSQ-RCO-IQ3_XXS] (ISTA file,
+#     −0.49 GB, MTP) and its -dflash text-only sibling; the research + verdicts live in that block.
+#     ⚠ llama.cpp 0.7.0 (b11669) = #30688, Vulkan draft decode 4× slower (compute buffer lands in GTT):
+#     hold fl at 0.6.0 until fixed — hits EVERY MTP preset here, not only this one.
+#   ✦ BUILD DATUM 2026-10-22 03:15 — fl turned out to be on 0.6.0 (b11429) + ggml-vulkan 0.25.3-2 (the
+#     SAME kernels as 10-02): bench 37.1 t/s / 21 pp / TTFT 3.3 / 14.4 used / 2.7 free @1.3 (-n 512).
+#     Server: 221 tok @ 37.07, draft acceptance 0.892 (141/158), mean len 2.78 → ~75 ms per
+#     speculative step vs ~173 on b11146 — a llama.cpp-side change (b11147..b11429), NOT the Vulkan
+#     kernels (ggml is a separate package, unchanged). A 4096-token think-run: 27.3 t/s @ acceptance
+#     0.51 / len 2.02 = the same ~74 ms step; acceptance sags over long thinking. Footprint 13.1,
+#     unchanged. → the ≥22 gate is PASSED 1.7× over; the 'clean-desktop specialty' verdict's SPEED half
+#     is obsolete (the VRAM half — never on a busy desktop — still stands). Role re-rank = user's call.
+#     03:25 re-run: 36.2 / 45 pp / TTFT 8.6 / 14.5 / 2.7 — reproducible.
+#     CAUSE (researched 10-22; a hypothesis — no PR in b11147..b11429 claims any such gain): Arch's llama-cpp
+#     links the SYSTEM ggml (-DLLAMA_USE_SYSTEM_GGML=ON), so every ggml-side Vulkan PR (#29476 GDN tune,
+#     #29280 descriptor reuse, FA work) is EXCLUDED — those ship in ggml 0.26.0, not on fl yet. Best fit:
+#     #29856 (10-03) "gather the recurrent states once so the reserve covers every split" — on 0.5.0 the
+#     hybrid graph was silently re-reserved after the first speculative step and the target compute
+#     buffer could land partly in GTT = the #30688 mechanism seen from the other side. The arithmetic
+#     agrees: the old no-MTP base (10.9 t/s = 92 ms/token) was SLOWER than today's whole MTP step (75 ms
+#     for ≥3 verified tokens + 2 draft passes), so the "10.9 base = the GDN kernel wall" story above is
+#     SUSPECT: that base was most likely GTT-starved, not kernel-bound. Cheap check whenever the card is
+#     free: a TEMP -nomtp alias on 0.6.0 — ~22–26 t/s confirms it, ~11 refutes it. #27694 (probabilistic
+#     drafter, 10-02) explains acceptance 0.84 → 0.89, not the step time. (Also learned: the 9B is hybrid
+#     too, 24 GDN + 8 attn per #30039 — the "regular-attention qwen35" remark further down is wrong.)
+#     ⚠ ggml 0.26.0 (the next -Syu brings ggml + ggml-vulkan 0.26.0-1, SOVERSION-compatible, unrebuilt):
+#     #30039 reports −45 % PREFILL on a GDN hybrid with b11429 binaries, TG flat → bench this preset right
+#     before and after that upgrade; if prefill tanks, downgrade ggml/ggml-vulkan from the pacman cache.
+#     REFERENCE from here: 37.1 (b11429). Every other MTP/hybrid preset needs a re-sweep on this build.
 #   ⚠ Needs a CURRENT llama.cpp build: first "qwen35" file HERE with ssm.*/hybrid-attn keys
 #   (the 9B is regular-attention qwen35). If the load fails with unknown-architecture /
 #   missing-tensor errors, update llama.cpp on fl before touching this preset.
@@ -418,6 +448,150 @@ min-p              = 0
 jinja              = on
 sleep-idle-seconds = 120
 
+# ═══ QUANT RACE 2026-10-22 — Qwen3.8-27B third-party 3-bit quants + DFlash2 (bench-only, NOT client-wired) ═══
+# Trigger: r/LocalLLaMA 2026-09-24 "Qwen-3.8-27B is good enough that I stopped using API": a 16 GB user
+#   (RTX 5060 Ti, CUDA, PCIe 5.0 x8, display on the iGPU) runs ByteShape IQ4_XS + DFlash2 + Raymond's
+#   KV-cache streaming; a reply says "try the ISTA IQ3_S / XXS — more speed and context, couldn't tell a
+#   difference in quality". What survives contact with THIS box (16 GB + display, Vulkan/RADV, PCIe 4.0 x8):
+#   · KV-cache streaming (troed → RaymondHuang210129/llama.cpp-adaptive-kv-streaming): OUT. CUDA-only —
+#     the README lists Vulkan as "memory-infrastructure tests only" (no attention path), ROCm = one
+#     unreviewed PR for gfx1201; both authors say PCIe 5.0 is required (PCIe 4.0 users: 2–4 t/s @192k);
+#     no upstream PR (discussion #28216 only). And it is a 160k+ tool — clients run this model at 24k.
+#   · ByteShape (byteshape/Qwen3.8-27B-GGUF, proprietary "ShapeLearn" per-tensor mixed types, the IQ*
+#     labels are size classes; MTP head kept, quantized IQ3/IQ4 vs Q6_K/Q8_0 elsewhere): IQ4_XS-3.84bpw
+#     13.08 GB → OUT (ceiling here ≈ 11 GB file); the commenter's own file is troed's 12.25 GB
+#     ASCII-vocab-pruned build (248320 → 129006 tokens) → OUT twice. Same size class as the incumbent:
+#     IQ3_S-3.23bpw 11.035 GB (vendor blog: 98.7 % of BF16 task avg vs 93.6 % for unsloth UD-IQ3_XXS —
+#     vendor numbers; the one independent KLD run ranks their IQ4_XS BELOW unsloth's UD-IQ4_XS, 0.050 vs
+#     0.019), IQ3_XS-3.01bpw 10.353 GB, IQ3_XXS-2.88bpw 9.919 GB. Optional third runner, see below.
+#   · ISTA (ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF: GSQ = learned per-coordinate grids, RCO = per-tensor
+#     type under a size budget, standard GGUF block types, imatrix ~90 % English — discussion #7 reports
+#     degraded Chinese; "-mtp" files carry the head, +0.35 GB, weights identical):
+#     IQ3_S-mtp 12.12 GB → footprint ≈ 14.2 → ~1.4 free @1.6 = UNDER THE 1.5 FLOOR. Plain IQ3_S 11.77
+#     fits only WITHOUT any drafter (~3.4 free) at ~10 t/s → no. Both reddit comments measured "more
+#     speed and context" against a 13 GB file, not against a 3-bit one.
+#     IQ3_XXS-mtp 10.443 GB = 0.49 GB under the incumbent → the one ISTA file with a case here.
+#     Quality evidence (nobody measured it against OUR unsloth v3 file): ISTA card wiki-ppl 7.20 vs
+#     BF16 7.05, AIME25/GPQA-D/LCBv6 within 1–2 pts of BF16; ByteShape's blog scores it 94.4 vs 93.6
+#     for UD-IQ3_XXS (= equal); Agention's KLD table puts it at 0.11, ~2× their own IQ3_XXS. Thread:
+#     one user "ISTA even at lower quants did better", troed "tried it, not as good for my use".
+#     → bench.py settles speed + VRAM only; the quality half is the user's own prompts, both files.
+#   · DFlash2 (z-lab/Qwen3.8-27B-DFlash2-GGUF: 1.92B block-diffusion drafter, 5 layers, 2048-token
+#     sliding window, no own embeddings/output head; Q4_K_M 1.143 GB; llama.cpp support since b10658 =
+#     already in fl's b11146): acceptance length ~5.4 vs the MTP head's 2.6 here. RDNA3/Vulkan reports
+#     (PR #27342 thread): 7900 XTX RADV n-max 3 = +4–12 % decode over MTP, prefill −1 to −12 %; Strix
+#     Halo RADV n-max 4 = 19–23 t/s vs MTP 20; R9700 n-max 4 = 52 vs 47; a net LOSS once layers spill.
+#     Expect +5–15 % over the incumbent (37.1 on b11429, 10-22), NOT the paper's 1.8× — every verified draft token
+#     re-runs the 48 GDN layers. Acceptance falls with context (5090 datum: 31–36 % at 23–63k vs MTP
+#     55 %) = why the redditor says "at low context".
+#     VRAM: drafter 1.14 GB + (1 + n-max) × ~150 MiB recurrent-state snapshots (n-max 3 ≈ 0.6 GB) +
+#     drafter KV — the MTP head measured 1.5 GB against a ~0.7 estimate, so budget ~2 GB and let the
+#     bench.py guard decide; the ISTA file's −0.49 GB is what buys the margin. Default n-max 7 = OUT.
+#     Text-only: #27408 (spec + mmproj → image requests 500) still open → NO mmproj on that preset.
+#     #28158 (Vulkan: draft token id 248320 → HTTP 500, rare, very long prompts) still open.
+#     Build window: #29226 (b11132) broke drafters WITH embeddings but WITHOUT an output head (fixed by
+#     #30111, b11512); the z-lab drafter has neither → should not be hit. FIRST GATE regardless:
+#     "draft acceptance" in the server log > 0 (0.00 = that class of breakage → drop the sibling).
+#   ⚠ BUILD: fl = llama-cpp 0.6.0-1 (b11429) + ggml 0.25.3-2 + ggml-vulkan 0.25.3-2, CONFIRMED 10-22 (the
+#     b11146 → b11429 move alone took the incumbent 15.5 → 37.1, see its block). Arch extra also has
+#     ggml/ggml-vulkan 0.26.0 (#27952 int8 coopmat prefill, #29476 GDN tune) — the next -Syu brings them
+#     = another variable, bench before/after. Upstream 0.7.0 (b11669) = #30688: Vulkan
+#     draft-mtp decode 4× / prefill 6× SLOWER, the target compute buffer re-allocated into GTT — on this
+#     box that is the freeze precursor, and it hits every MTP preset on the roster. When
+#     `pacman -Si llama-cpp` on fl shows 0.7.0: HOLD (IgnorePkg = llama-cpp ggml ggml-vulkan) until fixed.
+#     Race on the current build first (one variable per run); the ggml 0.26.0 bump is a separate round.
+#   PLAN (clean baseline, -n 512, incumbent re-run in the SAME session — the 10-02 band was 12.5–15.5):
+#     1. download (below) · 2. `sudo systemctl restart llama.service` ·
+#     3. ./bench.py -n 512 -m Qwen3.8-27B-UD-IQ3_XXS,Qwen3.8-27B-GSQ-RCO-IQ3_XXS,Qwen3.8-27B-GSQ-RCO-IQ3_XXS-dflash
+#     4. quality: the same 3–4 real prompts (incl. non-English) against incumbent vs GSQ.
+#   GATE: GSQ-mtp ≥ incumbent decode (expected ~+4 %) with free ≥ 2.5 → quality is the user's call →
+#     if it wins, either point the incumbent section's `model =` at the GSQ file (keeps the client id,
+#     accepted misnomer) or rename = the seven-client-file round. DFlash sibling: acceptance > 0 AND
+#     decode ≥ 1.10 × the SAME-SESSION incumbent AND free ≥ 2.5 → keep as the text-only fast sibling
+#     (wire into clients then); else drop. Loser files: delete from ~/software/models (10.4 + 1.1 GB).
+#   ✦ RACE RUN 2026-10-22 03:25 @1.3 baseline, -n 512, all three in ONE session (rows in bench-history.md):
+#     incumbent UD-IQ3_XXS ....... 36.2 t/s / 45 pp / TTFT 8.6 / 14.5 used / 2.7 free
+#     GSQ-RCO-IQ3_XXS (MTP) ...... 37.5 / 44 / 7.0 / 14.0 / 3.2 → +3.6 % decode, +0.5 GB free = exactly the
+#       file-size prediction. Speed + VRAM half of the gate PASSED. OPEN: the quality half (same 3–4 real
+#       prompts, one non-English, against both; nobody has measured ISTA vs unsloth v3 at this size).
+#     GSQ -dflash ................ 15.4 / 32 / 18.0 / 15.3 / 1.9 → −59 % vs its own MTP row and under the
+#       2.5 target → DROPPED (tombstone below). Read the acceptance line once: `journalctl -u llama.service
+#       --since 03:25 | grep 'draft acceptance'` — 0.00 = the #29226-window bug (fix #30111 = b11512 sits in
+#       0.7.0 behind #30688 → re-probe only on a fixed 0.7.x); > 0 = block-drafting re-runs the 48 GDN
+#       layers per verified block and loses on this card (the RX 9070 XT datum in #25117 said the same)
+#       → closed for good. Either way nothing to tune: n-max 2 only shrinks the loss.
+#     NEXT: quality call → if GSQ wins, point the incumbent's `model =` at the GSQ file (keeps the client
+#       id; the section name becomes a misnomer) or do the seven-client rename round, then delete the
+#       unsloth file; if not, delete the GSQ file and the section. The DFlash2 drafter can go now.
+# ⬇ DOWNLOAD on fl — curl straight into the models dir (the HF cache has root-owned dirs from docker):
+#   cd ~/software/models
+#   curl -L -o Qwen3.8-27B-GSQ-RCO-IQ3_XXS-mtp.gguf https://huggingface.co/ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF/resolve/main/Qwen3.8-27B-GSQ-RCO-IQ3_XXS-mtp.gguf
+#   (dropped 10-22, only for a re-probe) curl -L -o Qwen3.8-27B-DFlash2-Q4_K_M.gguf https://huggingface.co/z-lab/Qwen3.8-27B-DFlash2-GGUF/resolve/main/Qwen3.8-27B-DFlash2-Q4_K_M.gguf
+#   stat -c '%s %n' Qwen3.8-27B-GSQ-RCO-IQ3_XXS-mtp.gguf Qwen3.8-27B-DFlash2-Q4_K_M.gguf   # 10442827840 · 1143006816
+#   (mmproj: ISTA ships the same BF16 encoder — the existing mmproj-Qwen3.8-27B-F16.gguf is reused)
+
+[Qwen3.8-27B-GSQ-RCO-IQ3_XXS]
+# ⚗ RACE CANDIDATE 2026-10-22 — bench-only, NOT in any client file. = the incumbent preset with the ISTA
+#   file swapped in (MTP head Q6_K, same as unsloth's). Predicted @1.6 baseline @24k: ~14.1 used /
+#   ~3.0 free (incumbent 14.4 / 2.7), decode ~38–39 (incumbent 37.1 on b11429) — bandwidth × file size, nothing
+#   else moves. Knobs deliberately identical to the incumbent (n-max 2) for a clean A/B.
+#   ✓ MEASURED 2026-10-22 03:25 @1.3: 37.5 t/s / 44 pp / TTFT 7.0 / 14.0 used / 3.2 free (incumbent 36.2 /
+#   2.7 in the same run). Speed + VRAM passed; QUALITY CALL PENDING — not client-wired until then.
+model              = /home/anon/software/models/Qwen3.8-27B-GSQ-RCO-IQ3_XXS-mtp.gguf
+mmproj             = /home/anon/software/models/mmproj-Qwen3.8-27B-F16.gguf
+spec-type          = draft-mtp
+spec-draft-n-max   = 2
+ctx-size           = 24576
+n-gpu-layers       = 99
+threads            = 6
+flash-attn         = on
+cache-type-k       = q8_0
+cache-type-v       = q4_0
+batch-size         = 2048
+ubatch-size        = 256
+cache-reuse        = 256
+defrag-thold       = 0.1
+no-mmproj-offload  = true
+temp               = 1.0
+top-p              = 0.95
+top-k              = 20
+min-p              = 0
+jinja              = on
+sleep-idle-seconds = 120
+
+# ─── DROPPED 2026-10-22 03:25: [Qwen3.8-27B-GSQ-RCO-IQ3_XXS-dflash] (DFlash2 text-only sibling) ─────
+# 15.4 t/s / 32 pp / 15.3 used / 1.9 free vs 37.5 / 3.2 for the same file with its MTP head — the
+# z-lab block drafter is a net loss on this card (see the RACE RUN entry above for the two possible
+# causes and the only re-probe condition: a 0.7.x build that carries #30111 without #30688).
+# Removed as a loadable section on purpose: OWUI lists every router id, and 1.9 free on a busy
+# desktop is the GTT freeze. File can be deleted from the models dir: Qwen3.8-27B-DFlash2-Q4_K_M.gguf
+# Keys as benched (n-max 3, no mmproj — #27408):
+# model              = /home/anon/software/models/Qwen3.8-27B-GSQ-RCO-IQ3_XXS-mtp.gguf
+# model-draft        = /home/anon/software/models/Qwen3.8-27B-DFlash2-Q4_K_M.gguf
+# spec-type          = draft-dflash
+# spec-draft-n-max   = 3
+# ctx-size           = 24576
+# n-gpu-layers       = 99
+# threads            = 6
+# flash-attn         = on
+# cache-type-k       = q8_0
+# cache-type-v       = q4_0
+# batch-size         = 2048
+# ubatch-size        = 256
+# cache-reuse        = 256
+# defrag-thold       = 0.1
+# temp               = 1.0
+# top-p              = 0.95
+# top-k              = 20
+# min-p              = 0
+# jinja              = on
+# sleep-idle-seconds = 120
+
+# ─── optional 3rd runner (not added — copy the GSQ section if wanted): ByteShape IQ3_S-3.23bpw ────
+#   11.035 GB = the incumbent's size, vendor-claimed best quality in the class, MTP head kept (IQ3-quantized).
+#   model = /home/anon/software/models/Qwen3.8-27B-IQ3_S-3.23bpw.gguf
+#   curl -L -o Qwen3.8-27B-IQ3_S-3.23bpw.gguf https://huggingface.co/byteshape/Qwen3.8-27B-GGUF/resolve/main/Qwen3.8-27B-IQ3_S-3.23bpw.gguf   # 11035354496 B
+
 # ─── RETIRED 2026-07-16: [Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-IQ3_M] ──────────────
 # Dense: 10 t/s, 2.0 GB free (under the 2.5 target) and unfixable — bandwidth-bound, smaller
 # quant would cost the quality that justified it. Removed from opencode/pi/aichat.
@@ -552,6 +726,22 @@ sleep-idle-seconds = 30
 #     here "like the Thinking preset" silently disables the pi knob and brings back pi's
 #     "Response was truncated before completion." (= finish_reason length: think block + answer
 #     > the client's 4096 max_tokens). An instruct alias (budget 0) in a SEPARATE section is fine.
+#   ⚠ 2026-10-22: pi's "Compacting in OVERFLOW recovery" on this preset is NOT this window filling
+#     up — pi clamps each request's max_tokens to contextWindow − estimate − 4096, which on
+#     24k/4096 starts exactly at its compaction threshold; the first request after a compaction
+#     (estimate gains the system prompt + tool schemas) can leave the thinking reply ~1024 answer
+#     tokens → finish_reason length → pi compacts again and retries. Arithmetic + options in
+#     common/.pi/CLAUDE.md > Compaction tuning > max_tokens clamp.
+#     APPLIED 2026-10-22 (same day, unbenched): ctx-size 24576 → 32768 here + 32768 in the seven
+#     client files (pi contextWindow both blocks common+lw, opencode limit.context common+lw,
+#     aichat max_input_tokens 30000 common+lw+wm). Threshold and clamp in pi now sit at 24576,
+#     above anything a fresh post-compaction context reaches. Predicted cost ≈ 0.1 GB: hybrid
+#     GDN 3:1 = 10 attention layers with small GQA, ~8 KB/token of q8/q4 KV → ~70 MB for +8192,
+#     plus a few MB of FA scratch — read the "KV self size" line in the load log to confirm.
+#     GATE on the first load: `sudo systemctl restart llama.service`, then
+#     `./bench.py -m Ornith-1.5-35B-A3B-IQ3_XXS` — free ≥ 2.5 at the 2.0 baseline and decode
+#     ≈ 32 t/s → keep; else back to 24576 in all eight files (the router reads presets once at
+#     startup, and pi at 32k against a 24k server produces REAL overflow recoveries).
 # ⬇ DOWNLOAD from bartowski/Ornith-1.5-35B-A3B-GGUF (imatrix; the official repo has only Q4_K_M+
 #   ≥ 21.7 GB, unsloth has no 1.5 quants yet):
 #     Ornith-1.5-35B-A3B-IQ3_XXS.gguf     15,340,447,392 B · sha256 8918ccb9ee29abe3875efec0c3e86f0e35ef0b8a03e3f0e1c422869859a518d0
@@ -560,7 +750,9 @@ model              = /home/anon/software/models/Ornith-1.5-35B-A3B-IQ3_XXS.gguf
 mmproj             = /home/anon/software/models/mmproj-Ornith-1.5-35B-A3B-f16.gguf
 spec-type          = draft-mtp
 spec-draft-n-max   = 2
-ctx-size           = 24576       # = the daily driver; n_ctx_train 262144 — raise only after a bench
+ctx-size           = 32768       # 24576 → 32768 on 2026-10-22 for pi's max_tokens clamp (⚠ note above);
+                                 # UNBENCHED until the next restart — gate free ≥ 2.5 @2.0, decode unchanged;
+                                 # n_ctx_train 262144, KV is cheap here (hybrid GDN, ~8 KB/token)
 n-gpu-layers       = 99
 n-cpu-moe          = 16          # ✓ KEEP (09-21: 32.1 t/s, 13.8 used / 3.3 free @2.0; moe20 was 27.9 /
                                  # 12.4 / 4.8). = daily-driver envelope; moe14 not worth the margin.