refactor(paged): stock llama-cpp is patch-free; paged backend owns its patch series

Move ALL paged-attention content out of the stock backend/cpp/llama-cpp
backend and into backend/cpp/llama-cpp-localai-paged, so the stock backend is
pure upstream llama.cpp and the paged backend owns and applies its own vendored
patch series.

- Delete the dead early-exploration scaffold backend/cpp/llama-cpp/paged/
  (kernel/w4a16 Marlin scaffold, standalone paged_kv_manager, bench/loadgen,
  its own 0001-0002 patches, dense-era design docs, tests). Zero references
  repo-wide.
- Move backend/cpp/llama-cpp/patches/ (the 28-patch paged series + paged/README
  + 3 operational docs, plus the kernel/ scaffold patch and the top-level paged
  README/BENCHMARKS) to backend/cpp/llama-cpp-localai-paged/patches/. The stock
  backend keeps no patches/ dir; it had no non-paged base patches.
- Purify the stock backend: remove the LLAMA_PAGED make variable, the
  patches/paged apply loop, and the LLAMA_PAGED passthrough to prepare.sh;
  remove the paged-series handling from prepare.sh. The stock llama.cpp target
  now only clones the pin and applies its own (currently empty) base patches/
  series. The runtime paged option hooks in the shared grpc-server.cpp are
  untouched (inert without the patches).
- The paged backend's Makefile now applies its OWN patches/paged/0*.patch onto
  each freshly cloned tree via strict git apply (apply-paged-patches), after the
  copied stock infra clones the pin and applies base patches.
- Repoint every reference to the old patches/paged path: the upstream canary
  workflow + apply script, bump_deps.yaml, gallery/index.yaml, the docs,
  backend/index.yaml, backend-matrix.yml, the top-level Makefile comments, and
  the moved PIN_SYNC / README docs. Drop the now-removed LLAMA_PAGED=on
  build-toggle from comments.

Verified: the full 28-patch series applies strict-clean (git apply, exit 0) to
a clean ggml-org/llama.cpp checkout at the pinned c299a92c, and the repointed
canary apply script resolves and applies the series end to end.

Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

docs/content/features/backends.md

@@ -125,7 +125,7 @@ For getting started, see the available backends in LocalAI here: https://github.
 LocalAI supports various types of backends:
 
 - **LLM Backends**: For running language models (e.g., llama.cpp, vLLM, SGLang, transformers, MLX)
-  - **`llama-cpp-localai-paged`**: LocalAI's paged-attention llama.cpp variant - on-demand paged KV cache plus a decode-first prefill budget, tuned for NVFP4 dense/MoE on Blackwell/GB10. Same upstream llama.cpp pin as the stock `llama-cpp` backend, reusing its gRPC server; the paged engine is enabled per-model via the `paged_kv` / `max_batch_tokens` options. For Qwen3.5 gated-DeltaNet (hybrid SSM) models you can additionally set `options: [ssm_bf16_tau:<tokens>]` to enable the reduced-precision hybrid SSM-state fast mode: fast-decaying recurrent heads (memory length tau below the threshold, e.g. `32` / `64`) persist their state as bf16, halving that head's decode byte stream. Default off (`0`) keeps every head f32 and is bit-exact; when enabled the mode is **not** bit-exact (~91% same-top-p ceiling - see `backend/cpp/llama-cpp/patches/paged/README.md` for the quality/throughput profile).
+  - **`llama-cpp-localai-paged`**: LocalAI's paged-attention llama.cpp variant - on-demand paged KV cache plus a decode-first prefill budget, tuned for NVFP4 dense/MoE on Blackwell/GB10. Same upstream llama.cpp pin as the stock `llama-cpp` backend, reusing its gRPC server; the paged engine is enabled per-model via the `paged_kv` / `max_batch_tokens` options. For Qwen3.5 gated-DeltaNet (hybrid SSM) models you can additionally set `options: [ssm_bf16_tau:<tokens>]` to enable the reduced-precision hybrid SSM-state fast mode: fast-decaying recurrent heads (memory length tau below the threshold, e.g. `32` / `64`) persist their state as bf16, halving that head's decode byte stream. Default off (`0`) keeps every head f32 and is bit-exact; when enabled the mode is **not** bit-exact (~91% same-top-p ceiling - see `backend/cpp/llama-cpp-localai-paged/patches/paged/README.md` for the quality/throughput profile).
 - **Speech-to-Text Backends**: For transcription (e.g., whisper.cpp, parakeet.cpp, faster-whisper, NeMo)
 - **Text-to-Speech Backends**: For speech synthesis (e.g., piper, Kokoro, VibeVoice, Qwen3-TTS)
 - **Sound Generation Backends**: For music and audio generation (e.g., ACE-Step)