diff --git a/python/tvm/driver/tvmc/compiler.py b/python/tvm/driver/tvmc/compiler.py
index 2955df55432d..c24d36c432df 100644
--- a/python/tvm/driver/tvmc/compiler.py
+++ b/python/tvm/driver/tvmc/compiler.py
@@ -19,13 +19,14 @@
 """
 import logging
 import os.path
-from typing import Any, Optional, Dict, List, Union, Callable
+from typing import Any, Optional, Dict, List, Union, Callable, Sequence
 from pathlib import Path
 
 import tvm
 from tvm import autotvm, auto_scheduler
 from tvm import relay
 from tvm.driver.tvmc.registry import generate_registry_args, reconstruct_registry_entity
+from tvm.ir.instrument import PassInstrument
 from tvm.ir.memory_pools import WorkspaceMemoryPools
 from tvm.target import Target
 from tvm.relay.backend import Executor, Runtime
@@ -223,6 +224,7 @@ def compile_model(
     use_vm: bool = False,
     mod_name: Optional[str] = "default",
     workspace_pools: Optional[WorkspaceMemoryPools] = None,
+    instruments: Optional[Sequence[PassInstrument]] = None,
 ):
     """Compile a model from a supported framework into a TVM module.
 
@@ -277,6 +279,8 @@ def compile_model(
     workspace_pools: WorkspaceMemoryPools, optional
         Specification of WorkspacePoolInfo objects to be used as workspace memory in the
         compilation.
+    instruments: Optional[Sequence[PassInstrument]]
+        The list of pass instrument implementations.
 
     Returns
     -------
@@ -316,7 +320,10 @@ def compile_model(
             with auto_scheduler.ApplyHistoryBest(tuning_records):
                 config["relay.backend.use_auto_scheduler"] = True
                 with tvm.transform.PassContext(
-                    opt_level=opt_level, config=config, disabled_pass=disabled_pass
+                    opt_level=opt_level,
+                    config=config,
+                    disabled_pass=disabled_pass,
+                    instruments=instruments,
                 ):
                     logger.debug("building relay graph with autoscheduler")
                     graph_module = build(
@@ -332,7 +339,10 @@ def compile_model(
         else:
             with autotvm.apply_history_best(tuning_records):
                 with tvm.transform.PassContext(
-                    opt_level=opt_level, config=config, disabled_pass=disabled_pass
+                    opt_level=opt_level,
+                    config=config,
+                    disabled_pass=disabled_pass,
+                    instruments=instruments,
                 ):
                     logger.debug("building relay graph with tuning records")
                     graph_module = build(
@@ -347,7 +357,7 @@ def compile_model(
                     )
     else:
         with tvm.transform.PassContext(
-            opt_level=opt_level, config=config, disabled_pass=disabled_pass
+            opt_level=opt_level, config=config, disabled_pass=disabled_pass, instruments=instruments
         ):
             logger.debug("building relay graph (no tuning records provided)")
             graph_module = build(
diff --git a/tests/python/driver/tvmc/test_compiler.py b/tests/python/driver/tvmc/test_compiler.py
index 5535fc02249f..7cb50dd0e366 100644
--- a/tests/python/driver/tvmc/test_compiler.py
+++ b/tests/python/driver/tvmc/test_compiler.py
@@ -516,6 +516,7 @@ def test_compile_check_configs_composite_target(mock_pkg, mock_pc, mock_fe, mock
         config={"relay.ext.mock.options": {"testopt": "value"}},
         opt_level=3,
         disabled_pass=None,
+        instruments=None,
     )
     mock_pc.assert_has_calls(
         [
@@ -697,5 +698,27 @@ def test_compile_check_workspace_pools(mock_pkg, mock_fe, mock_relay):
     assert mock_relay.call_args_list[0][1]["workspace_memory_pools"] == memory_pools
 
 
+def test_compile_check_pass_instrument(keras_resnet50):
+    pytest.importorskip("tensorflow")
+
+    @tvm.instrument.pass_instrument
+    class PassesCounter:
+        def __init__(self):
+            self.run_before_count = 0
+            self.run_after_count = 0
+
+        def run_before_pass(self, mod, info):
+            self.run_before_count = self.run_before_count + 1
+
+        def run_after_pass(self, mod, info):
+            self.run_after_count = self.run_after_count + 1
+
+    passes_counter = PassesCounter()
+    tvmc_model = tvmc.load(keras_resnet50)
+    tvmc.compile(tvmc_model, target="llvm", instruments=[passes_counter])
+    assert passes_counter.run_after_count > 0
+    assert passes_counter.run_after_count == passes_counter.run_before_count
+
+
 if __name__ == "__main__":
     tvm.testing.main()