diff --git a/backend/tests/test_node_model_selection.py b/backend/tests/test_node_model_selection.py
new file mode 100644
index 0000000..bfb3f76
--- /dev/null
+++ b/backend/tests/test_node_model_selection.py
@@ -0,0 +1,126 @@
+import pytest
+from unittest.mock import MagicMock, patch
+from ea_chatbot.graph.nodes.query_analyzer import query_analyzer_node
+from ea_chatbot.graph.nodes.planner import planner_node
+from ea_chatbot.graph.nodes.reflector import reflector_node
+from ea_chatbot.graph.nodes.synthesizer import synthesizer_node
+from ea_chatbot.graph.workers.data_analyst.nodes.coder import coder_node as analyst_coder
+from ea_chatbot.graph.workers.researcher.nodes.searcher import searcher_node as researcher_searcher
+from ea_chatbot.graph.state import AgentState
+from ea_chatbot.graph.workers.data_analyst.state import WorkerState as AnalystState
+from ea_chatbot.graph.workers.researcher.state import WorkerState as ResearcherState
+from ea_chatbot.config import Settings
+
+@pytest.fixture
+def mock_settings():
+    settings = Settings()
+    settings.query_analyzer_llm.model = "model-qa"
+    settings.planner_llm.model = "model-planner"
+    settings.reflector_llm.model = "model-reflector"
+    settings.synthesizer_llm.model = "model-synthesizer"
+    settings.coder_llm.model = "model-coder"
+    settings.researcher_llm.model = "model-researcher"
+    return settings
+
+@patch("ea_chatbot.graph.nodes.query_analyzer.get_llm_model")
+@patch("ea_chatbot.graph.nodes.query_analyzer.Settings")
+def test_query_analyzer_model(mock_settings_cls, mock_get_llm, mock_settings):
+    mock_settings_cls.return_value = mock_settings
+    mock_llm = MagicMock()
+    mock_get_llm.return_value = mock_llm
+    
+    state = AgentState(question="test", messages=[], checklist=[], current_step=0, iterations=0, vfs={}, plots=[], dfs={}, next_action="", analysis={})
+    
+    try:
+        query_analyzer_node(state)
+    except:
+        pass # We only care about the call
+    
+    # Verify it was called with the QA config
+    args = mock_get_llm.call_args[0][0]
+    assert args.model == "model-qa"
+
+@patch("ea_chatbot.graph.nodes.planner.get_llm_model")
+@patch("ea_chatbot.graph.nodes.planner.Settings")
+def test_planner_model(mock_settings_cls, mock_get_llm, mock_settings):
+    mock_settings_cls.return_value = mock_settings
+    mock_llm = MagicMock()
+    mock_get_llm.return_value = mock_llm
+    
+    state = AgentState(question="test", messages=[], checklist=[], current_step=0, iterations=0, vfs={}, plots=[], dfs={}, next_action="", analysis={})
+    
+    try:
+        planner_node(state)
+    except:
+        pass
+    
+    args = mock_get_llm.call_args[0][0]
+    assert args.model == "model-planner"
+
+@patch("ea_chatbot.graph.nodes.reflector.get_llm_model")
+@patch("ea_chatbot.graph.nodes.reflector.Settings")
+def test_reflector_model(mock_settings_cls, mock_get_llm, mock_settings):
+    mock_settings_cls.return_value = mock_settings
+    mock_llm = MagicMock()
+    mock_get_llm.return_value = mock_llm
+    
+    state = AgentState(question="test", messages=[], checklist=[{"task": "T1"}], current_step=0, iterations=0, vfs={}, plots=[], dfs={}, next_action="", analysis={}, summary="Worker did X")
+    
+    try:
+        reflector_node(state)
+    except:
+        pass
+    
+    args = mock_get_llm.call_args[0][0]
+    assert args.model == "model-reflector"
+
+@patch("ea_chatbot.graph.nodes.synthesizer.get_llm_model")
+@patch("ea_chatbot.graph.nodes.synthesizer.Settings")
+def test_synthesizer_model(mock_settings_cls, mock_get_llm, mock_settings):
+    mock_settings_cls.return_value = mock_settings
+    mock_llm = MagicMock()
+    mock_get_llm.return_value = mock_llm
+    
+    state = AgentState(question="test", messages=[], checklist=[], current_step=0, iterations=0, vfs={}, plots=[], dfs={}, next_action="", analysis={})
+    
+    try:
+        synthesizer_node(state)
+    except:
+        pass
+    
+    args = mock_get_llm.call_args[0][0]
+    assert args.model == "model-synthesizer"
+
+@patch("ea_chatbot.graph.workers.data_analyst.nodes.coder.get_llm_model")
+@patch("ea_chatbot.graph.workers.data_analyst.nodes.coder.Settings")
+def test_analyst_coder_model(mock_settings_cls, mock_get_llm, mock_settings):
+    mock_settings_cls.return_value = mock_settings
+    mock_llm = MagicMock()
+    mock_get_llm.return_value = mock_llm
+    
+    state = AnalystState(task="test", messages=[], iterations=0, vfs_state={}, plots=[], result=None, code=None, output=None, error=None)
+    
+    try:
+        analyst_coder(state)
+    except:
+        pass
+    
+    args = mock_get_llm.call_args[0][0]
+    assert args.model == "model-coder"
+
+@patch("ea_chatbot.graph.workers.researcher.nodes.searcher.get_llm_model")
+@patch("ea_chatbot.graph.workers.researcher.nodes.searcher.Settings")
+def test_researcher_searcher_model(mock_settings_cls, mock_get_llm, mock_settings):
+    mock_settings_cls.return_value = mock_settings
+    mock_llm = MagicMock()
+    mock_get_llm.return_value = mock_llm
+    
+    state = ResearcherState(task="test", messages=[], iterations=0, result=None, queries=[], raw_results=[])
+    
+    try:
+        researcher_searcher(state)
+    except:
+        pass
+    
+    args = mock_get_llm.call_args[0][0]
+    assert args.model == "model-researcher"