diff --git a/flash/troubleshooting.mdx b/flash/troubleshooting.mdx
index 9547a85b..781e1d39 100644
--- a/flash/troubleshooting.mdx
+++ b/flash/troubleshooting.mdx
@@ -420,6 +420,47 @@ Failed to deserialize result: [error]
 
 3. **Check argument types**: Input arguments must also be serializable.
 
+### Payload too large
+
+**Error:**
+```
+Payload size X MB exceeds limit of 10.0 MB
+```
+
+**Cause:** The serialized argument exceeds the 10 MB limit. Flash uses base64 encoding, which expands data by approximately 33%, so roughly 7.5 MB of raw data becomes 10 MB when encoded.
+
+**Solutions:**
+
+1. **Use network volumes for large data**: Save large data to a network volume and pass the file path:
+   ```python
+   @Endpoint(name="processor", gpu=GpuGroup.ANY, volume="vol_abc123")
+   async def process(file_path: str) -> dict:
+       import numpy as np
+       data = np.load(file_path)  # Load from volume
+       return {"result": process_data(data)}
+   ```
+
+2. **Compress data before sending**: For data that must be passed directly, use compression:
+   ```python
+   import gzip
+
+   compressed = gzip.compress(data.tobytes())
+   # Pass compressed bytes instead
+   ```
+
+3. **Split large requests**: Break large datasets into smaller chunks and process them in multiple requests.
+
+### Deserialization timeout
+
+**Error:**
+```
+Deserialization timed out after 30s
+```
+
+**Cause:** The deserialization process took longer than 30 seconds. This usually indicates malformed or corrupted serialized data that causes the unpickle operation to hang.
+
+**Solution:** Verify your input data is properly serialized. If you're manually constructing payloads, ensure the data was serialized using `cloudpickle` and encoded with base64. The Flash SDK handles this automatically for programmatic calls.
+
 ### Circuit breaker open
 
 **Error:**