diff --git a/.openclaw-sync/source.json b/.openclaw-sync/source.json
index 88e81bfab..120573d48 100644
--- a/.openclaw-sync/source.json
+++ b/.openclaw-sync/source.json
@@ -1,5 +1,5 @@
 {
   "repository": "openclaw/openclaw",
-  "sha": "0a076bc0fca22e2a71bbc600b6f8bed7ee235408",
-  "syncedAt": "2026-04-27T12:23:35.776Z"
+  "sha": "750c180a6ca023a2bd9aebac6fffb65f2b0e6663",
+  "syncedAt": "2026-04-27T12:25:22.040Z"
 }
diff --git a/docs/gateway/local-models.md b/docs/gateway/local-models.md
index 8e36625ec..842f9a081 100644
--- a/docs/gateway/local-models.md
+++ b/docs/gateway/local-models.md
@@ -11,6 +11,10 @@ Local is doable, but OpenClaw expects large context + strong defenses against pr
 
 If you want the lowest-friction local setup, start with [LM Studio](/providers/lmstudio) or [Ollama](/providers/ollama) and `openclaw onboard`. This page is the opinionated guide for higher-end local stacks and custom OpenAI-compatible local servers.
 
+<Warning>
+**WSL2 + Ollama + NVIDIA/CUDA users:** The official Ollama Linux installer enables a systemd service with `Restart=always`. On WSL2 GPU setups, autostart can reload the last model during boot and pin host memory. If your WSL2 VM repeatedly restarts after enabling Ollama, see [WSL2 crash loop](/providers/ollama#wsl2-crash-loop-repeated-reboots).
+</Warning>
+
 ## Recommended: LM Studio + large local model (Responses API)
 
 Best current local stack. Load a large model in LM Studio (for example, a full-size Qwen, DeepSeek, or Llama build), enable the local server (default `http://127.0.0.1:1234`), and use Responses API to keep reasoning separate from final text.
diff --git a/docs/providers/ollama.md b/docs/providers/ollama.md
index 802154382..c189c976e 100644
--- a/docs/providers/ollama.md
+++ b/docs/providers/ollama.md
@@ -897,6 +897,41 @@ For the full setup and behavior details, see [Ollama Web Search](/tools/ollama-s
 ## Troubleshooting
 
 <AccordionGroup>
+  <Accordion title="WSL2 crash loop (repeated reboots)">
+    On WSL2 with NVIDIA/CUDA, the official Ollama Linux installer creates an `ollama.service` systemd unit with `Restart=always`. If that service autostarts and loads a GPU-backed model during WSL2 boot, Ollama can pin host memory while the model loads. Hyper-V memory reclaim cannot always reclaim those pinned pages, so Windows can terminate the WSL2 VM, systemd starts Ollama again, and the loop repeats.
+
+    Common evidence:
+
+    - repeated WSL2 reboots or terminations from the Windows side
+    - high CPU in `app.slice` or `ollama.service` shortly after WSL2 startup
+    - SIGTERM from systemd rather than a Linux OOM-killer event
+
+    OpenClaw logs a startup warning when it detects WSL2, `ollama.service` enabled with `Restart=always`, and visible CUDA markers.
+
+    Mitigation:
+
+    ```bash
+    sudo systemctl disable ollama
+    ```
+
+    Add this to `%USERPROFILE%\.wslconfig` on the Windows side, then run `wsl --shutdown`:
+
+    ```ini
+    [experimental]
+    autoMemoryReclaim=disabled
+    ```
+
+    Set a shorter keep-alive in the Ollama service environment, or start Ollama manually only when you need it:
+
+    ```bash
+    export OLLAMA_KEEP_ALIVE=5m
+    ollama serve
+    ```
+
+    See [ollama/ollama#11317](https://github.com/ollama/ollama/issues/11317).
+
+  </Accordion>
+
   <Accordion title="Ollama not detected">
     Make sure Ollama is running and that you set `OLLAMA_API_KEY` (or an auth profile), and that you did **not** define an explicit `models.providers.ollama` entry: