diff --git a/docs/llm.txt b/docs/llm.txt
index c6a7e85e..d6674264 100644
--- a/docs/llm.txt
+++ b/docs/llm.txt
@@ -24393,7 +24393,6 @@ from swarms.structs.swarming_architectures import (
     exponential_swarm,
     fibonacci_swarm,
     grid_swarm,
-    linear_swarm,
     mesh_swarm,
     one_to_three,
     prime_swarm,
@@ -24634,7 +24633,6 @@ async def run_all_examples():
     
     # Finance examples
     run_finance_circular_swarm()
-    run_finance_linear_swarm()
     run_finance_mesh_swarm()
     run_mathematical_finance_swarms()
     
diff --git a/docs/swarms/examples/unique_swarms.md b/docs/swarms/examples/unique_swarms.md
index 245653af..af3b30e1 100644
--- a/docs/swarms/examples/unique_swarms.md
+++ b/docs/swarms/examples/unique_swarms.md
@@ -324,7 +324,6 @@ from swarms.structs.swarming_architectures import (
     exponential_swarm,
     fibonacci_swarm,
     grid_swarm,
-    linear_swarm,
     mesh_swarm,
     one_to_three,
     prime_swarm,
@@ -565,7 +564,6 @@ async def run_all_examples():
     
     # Finance examples
     run_finance_circular_swarm()
-    run_finance_linear_swarm()
     run_finance_mesh_swarm()
     run_mathematical_finance_swarms()
     
diff --git a/examples/multi_agent/utils/unique_swarms_examples.py b/examples/multi_agent/utils/unique_swarms_examples.py
index 6c315e25..09788cbf 100644
--- a/examples/multi_agent/utils/unique_swarms_examples.py
+++ b/examples/multi_agent/utils/unique_swarms_examples.py
@@ -8,7 +8,6 @@ from swarms.structs.swarming_architectures import (
     exponential_swarm,
     fibonacci_swarm,
     grid_swarm,
-    linear_swarm,
     mesh_swarm,
     one_to_three,
     prime_swarm,
@@ -263,7 +262,6 @@ async def run_all_examples():
 
     # Finance examples
     run_finance_circular_swarm()
-    run_finance_linear_swarm()
     run_finance_mesh_swarm()
     run_mathematical_finance_swarms()
 
diff --git a/swarms/structs/__init__.py b/swarms/structs/__init__.py
index ec292632..18f46c5c 100644
--- a/swarms/structs/__init__.py
+++ b/swarms/structs/__init__.py
@@ -90,7 +90,6 @@ from swarms.structs.swarming_architectures import (
     geometric_swarm,
     grid_swarm,
     harmonic_swarm,
-    linear_swarm,
     log_swarm,
     mesh_swarm,
     one_to_one,
@@ -128,7 +127,6 @@ __all__ = [
     "geometric_swarm",
     "grid_swarm",
     "harmonic_swarm",
-    "linear_swarm",
     "log_swarm",
     "mesh_swarm",
     "one_to_one",
diff --git a/swarms/structs/various_alt_swarms.py b/swarms/structs/various_alt_swarms.py
index c4b34f9f..589e9ad2 100644
--- a/swarms/structs/various_alt_swarms.py
+++ b/swarms/structs/various_alt_swarms.py
@@ -119,60 +119,6 @@ class CircularSwarm(BaseSwarm):
         return self._format_return()
 
 
-class LinearSwarm(BaseSwarm):
-    """
-    Implements a linear swarm where agents process tasks sequentially.
-    """
-
-    def __init__(
-        self,
-        agents: AgentListType,
-        name: str = "LinearSwarm",
-        description: str = "A linear swarm where agents process tasks sequentially",
-        output_type: str = "dict",
-    ):
-        """
-        Initialize the LinearSwarm.
-
-        Args:
-            agents: List of Agent objects or nested list of Agent objects
-            name: Name of the swarm
-            description: Description of the swarm's purpose
-            output_type: Type of output format, one of 'dict', 'list', 'string', 'json', 'yaml', 'xml', etc.
-        """
-        super().__init__(agents, name, description, output_type)
-
-    def run(self, tasks: List[str]) -> Union[Dict, List, str]:
-        """
-        Run the linear swarm with the given tasks
-
-        Args:
-            tasks: List of tasks to be processed
-
-        Returns:
-            Union[Dict, List, str]: The conversation history in the requested format
-        """
-        if not self.agents or not tasks:
-            raise ValueError(
-                "Agents and tasks lists cannot be empty."
-            )
-
-        tasks_copy = tasks.copy()
-        responses = []
-
-        for agent in self.agents:
-            if tasks_copy:
-                task = tasks_copy.pop(0)
-                response = agent.run(task)
-                self.conversation.add(
-                    role=agent.agent_name,
-                    content=response,
-                )
-                responses.append(response)
-
-        return self._format_return()
-
-
 class StarSwarm(BaseSwarm):
     """
     Implements a star swarm where a central agent processes all tasks, followed by others.
diff --git a/tests/structs/test_swarm_architectures.py b/tests/structs/test_swarm_architectures.py
index cbe7d4d8..7be89129 100644
--- a/tests/structs/test_swarm_architectures.py
+++ b/tests/structs/test_swarm_architectures.py
@@ -8,7 +8,6 @@ from swarms.structs.swarming_architectures import (
     geometric_swarm,
     grid_swarm,
     harmonic_swarm,
-    linear_swarm,
     log_swarm,
     mesh_swarm,
     one_to_one,
@@ -69,21 +68,6 @@ def test_grid_swarm():
     assert len(result) > 0
 
 
-def test_linear_swarm():
-    """Test linear swarm sequential processing"""
-    agents = create_test_agents(3)
-    tasks = ["Research task", "Write content", "Review output"]
-
-    result = linear_swarm(agents, tasks)
-
-    assert isinstance(result, list)
-    assert len(result) > 0
-
-    for log in result:
-        assert "role" in log
-        assert "content" in log
-
-
 def test_star_swarm():
     """Test star swarm with central and peripheral agents"""
     agents = create_test_agents(4)