feat(llm): raise prompt cache RAM budget via --cache-ram

Log shows 253 prompt-cache evictions and 146 full ~42k re-prefills at the default budget.
Add LLAMA_CACHE_RAM and the throughput-tuning research note.

Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>

docs/architecture.md

@@ -25,6 +25,7 @@ The main model's backend. It is always running. Lazytainer used to idle-stop it,
 - **`LLAMA_PARALLEL`** is the backend's number of **slots**. It's kept low on purpose: more slots meant more contended prefill, which pushed requests past the gateway's timeouts ([gateway → Timeouts](gateway.md#timeouts)). Requests beyond the slot count wait in llama.cpp's own queue, which has no timeout. So the timeout that matters is the gateway's per-connection one.
 - **Per-slot context = `LLAMA_CTX_SIZE / LLAMA_PARALLEL`.** llama.cpp divides the context across slots, and each request gets one slot's share. Every coding CLI's context-window setting must use this number, not the raw context size. Real sessions already fill a large share of it, so check that the per-slot figure stays comfortably above observed usage before lowering either value.
 - **`--cache-reuse`** reuses cached KV for any matching prompt chunk instead of re-prefilling from scratch. That fixes the root cause behind the gateway's non-ping SSE timeout ([`research/omniroute-non-ping-sse-stream-timeout.md`](research/omniroute-non-ping-sse-stream-timeout.md)). It pairs with OmniRoute's prompt-cache affinity (a dashboard setting, on by default), which keeps a conversation on the same slot so that there is a matching prefix to reuse.
+- **`LLAMA_CACHE_RAM`** (`--cache-ram`, MiB) is the host-RAM budget for saved prompt-cache entries. When a slot is reused, llama.cpp parks the old prompt's state in RAM so it can be restored instead of re-prefilled. The llama.cpp default is too small for ~40k-token agent prompts (entries are ~2 GiB each), so entries got evicted and requests re-prefilled in full. Raising it is the only place spare DDR RAM helps; it does not speed up decode. Keep it well below the host's free RAM. Evidence and the A/B method: [`research/qwen3.8-27b-throughput-tuning.md`](research/qwen3.8-27b-throughput-tuning.md).
 - **`--jinja`** enables the chat template that tool calling depends on. Without it, tool-use requests fail outright.
 - **Tool-calling reliability** of this model family on llama.cpp has open upstream parser bugs: [`research/qwen3.8-27b-tool-calling.md`](research/qwen3.8-27b-tool-calling.md).
 - **Speculative decoding (DFlash2):** `--spec-type draft-dflash` with a separate drafter GGUF (`LLAMA_DRAFT_MODEL_FILE`), fetched by `downloader-draft`. It replaced MTP (draft heads inside the target GGUF). `LLAMA_SPEC_N_MAX` is the draft length. Upstream: [llama.cpp#27342](https://github.com/ggml-org/llama.cpp/pull/27342). Draft acceptance can collapse at high slot counts ([llama.cpp#27117](https://github.com/ggml-org/llama.cpp/issues/27117)), another reason `LLAMA_PARALLEL` stays low.