diff --git a/persistent-memory.md b/persistent-memory.md
index d30f7e2..7719bd8 100644
--- a/persistent-memory.md
+++ b/persistent-memory.md
@@ -138,6 +138,11 @@ _As of 2026-07-08 — OFF-THE-SHELF INFERENCE STACK is the active work (home-tra
   old AEON trace-not-surfacing gap). One-model fallback (Magidonia both, lighter reasoning) documented in the stack
   header/README. Requirements met: prose#1, ≥50tps#2, low-refusal#3, dense#4, GGUF-not-Ollama#5, fit-GPU0#6, thinking#7.
   Candidate GGUFs also on disk for A/B: Cydonia-R1-24B-v4.1, PaintedFantasy-v4.1-24B, RpR-v4 Q6_K.
+  **MAX CONTEXT (2026-07-08):** char-rp **96K** (Magidonia native 128K), char-rp-reasoning **40K** (QwQ native
+  40960, YaRN-free max), **q8_0 KV cache both** (near-lossless, ~2× ctx/GB; verified coherent, no Qwen gibberish).
+  GPU0 ~93/97G, ~4.3G margin (gen fixed-util + static KV → stable, won't OOM). 64/50 tps at max ctx. `kv_unified`
+  → a single conversation gets the FULL n_ctx (4 slots share the pool, not a /4 split). 128K char-rp only by
+  dropping the reasoning seat's ctx (shared GPU0 budget). Tunables: CHARRP_CTX / CHARRP_REASONING_CTX / *_KV_TYPE.
 
 - **⏳ PENDING — wire LiteLLM gateway sampling defaults for GEN** (operator: "wire those settings in"). Config:
   `ana-docker:/opt/docker/conf/litellm/config.yaml`. **gen (Qwen3.6)** — thinking
diff --git a/stacks/char-rp-gguf/.env.example b/stacks/char-rp-gguf/.env.example
index 0ca3670..8d957c6 100644
--- a/stacks/char-rp-gguf/.env.example
+++ b/stacks/char-rp-gguf/.env.example
@@ -24,7 +24,11 @@ CHARRP_PORT=8016
 CHARRP_MODEL=rp/TheDrummer_Magidonia-24B-v4.3-Q6_K.gguf
 # Alternate prose model (more literary flair, looser POV adherence) — uncomment to swap:
 # CHARRP_MODEL=rp/MS3.2-PaintedFantasy-v4.1-24B-Q6_K.gguf
-CHARRP_CTX=16384
+# Context. Magidonia native = 131072 (128K). 96K @ q8_0 KV ~ 8.4G VRAM; f16 KV doubles
+# that. Raise toward 131072 only if you drop the reasoning seat's ctx (shared GPU-0 budget).
+CHARRP_CTX=98304
+# KV cache dtype: q8_0 (~half VRAM, near-lossless) or f16 (max fidelity, 2x VRAM).
+CHARRP_KV_TYPE=q8_0
 
 # ── REASONING seat (char-rp-reasoning) ──────────────────────────────────────
 CHARRP_REASONING_CONTAINER=llama-charrp-reasoning
@@ -33,7 +37,10 @@ CHARRP_REASONING_PORT=8018
 # llama.cpp-managed CoT). ~50 tok/s @ Q5. Use Q6_K (~46 tok/s) for a touch more
 # quality if speed is not binding.
 CHARRP_REASONING_MODEL=rp/QwQ-32B-ArliAI-RpR-v4-Q5_K_M.gguf
-CHARRP_REASONING_CTX=16384
+# QwQ native ctx = 40960 (its max without YaRN). ~5.5G VRAM @ q8_0 KV.
+CHARRP_REASONING_CTX=40960
+# KV cache dtype (Qwen-arch): q8_0 verified coherent here; f16 if a future model gibbers.
+CHARRP_REASONING_KV_TYPE=q8_0
 # Thinking-token cap (QwQ over-thinks otherwise → starves the prose). 300-500 = a
 # concise, useful scene-plan before the response.
 CHARRP_REASONING_BUDGET=400
diff --git a/stacks/char-rp-gguf/compose.yaml b/stacks/char-rp-gguf/compose.yaml
index cedd0ef..9c47d6a 100644
--- a/stacks/char-rp-gguf/compose.yaml
+++ b/stacks/char-rp-gguf/compose.yaml
@@ -69,9 +69,15 @@ services:
       - --n-gpu-layers
       - "999"
       - --ctx-size
-      - "${CHARRP_CTX:-16384}"
+      - "${CHARRP_CTX:-98304}"
       - --flash-attn
       - on
+      # q8_0 KV cache ~halves KV VRAM (8-bit, near-lossless) → ~2x the context per GB.
+      # Mistral/Magistral handles q8 KV cleanly. Set f16 in .env to disable.
+      - --cache-type-k
+      - ${CHARRP_KV_TYPE:-q8_0}
+      - --cache-type-v
+      - ${CHARRP_KV_TYPE:-q8_0}
       - --jinja
     healthcheck:
       test: ["CMD-SHELL", "curl -fsS http://localhost:8080/health >/dev/null || exit 1"]
@@ -115,9 +121,16 @@ services:
       - --n-gpu-layers
       - "999"
       - --ctx-size
-      - "${CHARRP_REASONING_CTX:-16384}"
+      - "${CHARRP_REASONING_CTX:-40960}"
       - --flash-attn
       - on
+      # QwQ native ctx = 40960 (beyond needs YaRN → quality loss; don't). Qwen-arch can be
+      # KV-quant-sensitive: q8_0 is verified coherent here, but flip to f16 in .env if a
+      # future model shows gibberish.
+      - --cache-type-k
+      - ${CHARRP_REASONING_KV_TYPE:-q8_0}
+      - --cache-type-v
+      - ${CHARRP_REASONING_KV_TYPE:-q8_0}
       - --jinja
       # QwQ reasoning is template-native → llama.cpp manages it. --reasoning on surfaces
       # the trace in reasoning_content (content stays clean prose); --reasoning-budget