feat(llama.cpp): raise default context to 128K, document RAM/SSD offload knobs

LLAMA_CTX_SIZE default 65536 -> 131072: real usage was burning through 64K
fast. ~25.6GB VRAM (17.6GB weights + ~8GB KV cache) on the 32GB R9700,
~6GB headroom — see docs/research/qwen3.8-27b-quant.md for the full table.

Also documents LLAMA_GPU_LAYERS as the RAM-offload knob for this dense
model (no separate RAM-offload flag exists in llama.cpp, and --n-cpu-moe/
--cpu-moe/--override-tensor "exps" are MoE-only, no-ops here), and that
there's no explicit SSD offload tier to enable — llama.cpp's default mmap
already falls back to disk implicitly if GPU+RAM run out.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FCAUsjGNSoJTtK8hyLKg5m

docker-compose.yml

@@ -18,7 +18,7 @@ services:
       --host 0.0.0.0
       --port 8080
       --n-gpu-layers ${LLAMA_GPU_LAYERS:-999}
-      --ctx-size ${LLAMA_CTX_SIZE:-65536}
+      --ctx-size ${LLAMA_CTX_SIZE:-131072}
       --jinja
     # No published host port: llama-server is reached only via the litellm
     # proxy on the ai-stack docker network now — see issue #15. Its