diff --git a/bitsandbytes/optim/optimizer.py b/bitsandbytes/optim/optimizer.py
index 5f31a584e..db7a35231 100644
--- a/bitsandbytes/optim/optimizer.py
+++ b/bitsandbytes/optim/optimizer.py
@@ -111,6 +111,8 @@ def register_module_override(self, module, param_name, config):
 
 
 class Optimizer8bit(torch.optim.Optimizer):
+    _FSDP_WRAPPED_QUANT_STATE_KEY = "__bnb_optimizer_quant_state__"
+
     def __init__(self, params, defaults, optim_bits=32, is_paged=False):
         """
         Base 8-bit optimizer class.
@@ -152,6 +154,34 @@ def fill_qmap(self):
         self.name2qmap["dynamic"] = F.create_dynamic_map(signed=True)
         self.name2qmap["udynamic"] = F.create_dynamic_map(signed=False)
 
+    def state_dict(self):
+        """Return optimizer state, wrapping quantization tensors for FSDP compatibility.
+
+        FSDP's full_optim_state_dict gathers all tensor states across ranks.
+        Quantization states (state1, state2, absmax, etc.) have different shapes
+        than model parameters, causing gather operations to fail. By wrapping
+        these tensors in a nested dict, FSDP skips them during gathering.
+        """
+        state_dict = super().state_dict()
+
+        # Deep copy the state to avoid modifying the original optimizer state
+        # PyTorch's state_dict() only does a shallow copy
+        state_dict["state"] = {
+            k: {kk: vv for kk, vv in v.items()} if isinstance(v, dict) else v for k, v in state_dict["state"].items()
+        }
+
+        # Wrap quantization-specific tensors in a nested dict to hide from FSDP
+        for param_state in state_dict["state"].values():
+            if isinstance(param_state, dict):
+                quant_state = {}
+                keys_to_wrap = [k for k in param_state if k in self.non_castable_tensor_keys]
+                for key in keys_to_wrap:
+                    quant_state[key] = param_state.pop(key)
+                if quant_state:
+                    param_state[self._FSDP_WRAPPED_QUANT_STATE_KEY] = quant_state
+
+        return state_dict
+
     def __setstate__(self, state):
         super().__setstate__(state)
 
@@ -166,6 +196,13 @@ def load_state_dict(self, state_dict, move_to_device=True):
         """
         # deepcopy, to be consistent with module API
         state_dict = deepcopy(state_dict)
+
+        # Unwrap quantization states that were wrapped for FSDP compatibility
+        for param_state in state_dict["state"].values():
+            if isinstance(param_state, dict) and self._FSDP_WRAPPED_QUANT_STATE_KEY in param_state:
+                quant_state = param_state.pop(self._FSDP_WRAPPED_QUANT_STATE_KEY)
+                param_state.update(quant_state)
+
         # Validate the state_dict
         groups = self.param_groups
         saved_groups = state_dict["param_groups"]