diff --git a/ax/benchmark/problems/surrogate.py b/ax/benchmark/problems/surrogate.py
deleted file mode 100644
index 6c188540801..00000000000
--- a/ax/benchmark/problems/surrogate.py
+++ /dev/null
@@ -1,33 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-# pyre-strict
-"""
-Benchmark problem based on surrogate.
-
-This problem class might appear to function identically to its non-surrogate
-counterpart, `BenchmarkProblem`, aside from the restriction that its runners is
-of type `SurrogateRunner`. However, it is treated specially within JSON storage
-because surrogates cannot be easily serialized.
-"""
-
-from dataclasses import dataclass, field
-
-from ax.benchmark.benchmark_problem import BenchmarkProblem
-from ax.benchmark.runners.surrogate import SurrogateRunner
-
-
-@dataclass(kw_only=True)
-class SurrogateBenchmarkProblem(BenchmarkProblem):
-    """
-    Benchmark problem whose `runner` is a `SurrogateRunner`.
-
-    `SurrogateRunner` allows for the surrogate to be constructed lazily and for
-    datasets to be downloaded lazily.
-
-    For argument descriptions, see `BenchmarkProblem`.
-    """
-
-    runner: SurrogateRunner = field(repr=False)
diff --git a/ax/benchmark/tests/runners/test_botorch_test_problem.py b/ax/benchmark/tests/runners/test_botorch_test_problem.py
index 02d183722a8..c7d4e11c248 100644
--- a/ax/benchmark/tests/runners/test_botorch_test_problem.py
+++ b/ax/benchmark/tests/runners/test_botorch_test_problem.py
@@ -150,7 +150,7 @@ def test_synthetic_runner(self) -> None:
                     outcome_names = ["objective_0"]
             elif isinstance(test_problem, TestParamBasedTestProblem):
                 outcome_names = [f"objective_{i}" for i in range(num_outcomes)]
-            elif isinstance(test_problem, SurrogateTestFunction):
+            else:
                 outcome_names = ["branin"]
 
             # Set up runner
diff --git a/ax/benchmark/tests/runners/test_surrogate_runner.py b/ax/benchmark/tests/runners/test_surrogate_runner.py
index 099d09f2d5e..9ad256f7f90 100644
--- a/ax/benchmark/tests/runners/test_surrogate_runner.py
+++ b/ax/benchmark/tests/runners/test_surrogate_runner.py
@@ -8,15 +8,10 @@
 from unittest.mock import MagicMock, patch
 
 import torch
-from ax.benchmark.runners.surrogate import SurrogateRunner, SurrogateTestFunction
-from ax.core.parameter import ParameterType, RangeParameter
-from ax.core.search_space import SearchSpace
+from ax.benchmark.runners.surrogate import SurrogateTestFunction
 from ax.modelbridge.torch import TorchModelBridge
 from ax.utils.common.testutils import TestCase
-from ax.utils.testing.benchmark_stubs import (
-    get_soo_surrogate_legacy,
-    get_soo_surrogate_test_function,
-)
+from ax.utils.testing.benchmark_stubs import get_soo_surrogate_test_function
 
 
 class TestSurrogateTestFunction(TestCase):
@@ -84,84 +79,3 @@ def _construct_test_function(name: str) -> SurrogateTestFunction:
         self.assertEqual(runner_1, runner_1a)
         self.assertNotEqual(runner_1, runner_2)
         self.assertNotEqual(runner_1, 1)
-
-
-class TestSurrogateRunner(TestCase):
-    def setUp(self) -> None:
-        super().setUp()
-        self.search_space = SearchSpace(
-            parameters=[
-                RangeParameter("x", ParameterType.FLOAT, 0.0, 5.0),
-                RangeParameter("y", ParameterType.FLOAT, 1.0, 10.0, log_scale=True),
-                RangeParameter("z", ParameterType.INT, 1.0, 5.0, log_scale=True),
-            ]
-        )
-
-    def test_surrogate_runner(self) -> None:
-        # Construct a search space with log-scale parameters.
-        for noise_std in (0.0, 0.1, {"dummy_metric": 0.2}):
-            with self.subTest(noise_std=noise_std):
-                surrogate = MagicMock()
-                mock_mean = torch.tensor([[0.1234]], dtype=torch.double)
-                surrogate.predict = MagicMock(return_value=(mock_mean, 0))
-                surrogate.device = torch.device("cpu")
-                surrogate.dtype = torch.double
-                runner = SurrogateRunner(
-                    name="test runner",
-                    _surrogate=surrogate,
-                    _datasets=[],
-                    outcome_names=["dummy_metric"],
-                    noise_stds=noise_std,
-                )
-                self.assertEqual(runner.name, "test runner")
-                self.assertIs(runner.surrogate, surrogate)
-                self.assertEqual(runner.outcome_names, ["dummy_metric"])
-                self.assertEqual(runner.noise_stds, noise_std)
-
-    def test_lazy_instantiation(self) -> None:
-        runner = get_soo_surrogate_legacy().runner
-
-        self.assertIsNone(runner._surrogate)
-        self.assertIsNone(runner._datasets)
-
-        # Accessing `surrogate` sets datasets and surrogate
-        self.assertIsInstance(runner.surrogate, TorchModelBridge)
-        self.assertIsInstance(runner._surrogate, TorchModelBridge)
-        self.assertIsInstance(runner._datasets, list)
-
-        # Accessing `datasets` also sets datasets and surrogate
-        runner = get_soo_surrogate_legacy().runner
-        self.assertIsInstance(runner.datasets, list)
-        self.assertIsInstance(runner._surrogate, TorchModelBridge)
-        self.assertIsInstance(runner._datasets, list)
-
-        with patch.object(
-            runner,
-            "get_surrogate_and_datasets",
-            wraps=runner.get_surrogate_and_datasets,
-        ) as mock_get_surrogate_and_datasets:
-            runner.surrogate
-        mock_get_surrogate_and_datasets.assert_not_called()
-
-    def test_instantiation_raises_with_missing_args(self) -> None:
-        with self.assertRaisesRegex(
-            ValueError, "If `get_surrogate_and_datasets` is None, `_surrogate` and "
-        ):
-            SurrogateRunner(name="test runner", outcome_names=[], noise_stds=0.0)
-
-    def test_equality(self) -> None:
-        def _construct_runner(name: str) -> SurrogateRunner:
-            return SurrogateRunner(
-                name=name,
-                _surrogate=MagicMock(),
-                _datasets=[],
-                outcome_names=["dummy_metric"],
-                noise_stds=0.0,
-            )
-
-        runner_1 = _construct_runner("test 1")
-        runner_2 = _construct_runner("test 2")
-        runner_1a = _construct_runner("test 1")
-        self.assertEqual(runner_1, runner_1a)
-        self.assertNotEqual(runner_1, runner_2)
-        self.assertNotEqual(runner_1, 1)
diff --git a/ax/storage/json_store/registry.py b/ax/storage/json_store/registry.py
index 0cdb49c32b6..a798c30b1fe 100644
--- a/ax/storage/json_store/registry.py
+++ b/ax/storage/json_store/registry.py
@@ -370,8 +370,6 @@
     "SumConstraint": SumConstraint,
     "Surrogate": Surrogate,
     "SurrogateMetric": BenchmarkMetric,  # backward-compatiblity
-    # NOTE: SurrogateRunners -> SyntheticRunner on load due to complications
-    "SurrogateRunner": SyntheticRunner,
     "SobolQMCNormalSampler": SobolQMCNormalSampler,
     "SyntheticRunner": SyntheticRunner,
     "SurrogateSpec": SurrogateSpec,
diff --git a/ax/utils/testing/benchmark_stubs.py b/ax/utils/testing/benchmark_stubs.py
index 60244511b6b..f5a7a72b717 100644
--- a/ax/utils/testing/benchmark_stubs.py
+++ b/ax/utils/testing/benchmark_stubs.py
@@ -15,12 +15,11 @@
 from ax.benchmark.benchmark_metric import BenchmarkMetric
 from ax.benchmark.benchmark_problem import BenchmarkProblem, create_problem_from_botorch
 from ax.benchmark.benchmark_result import AggregatedBenchmarkResult, BenchmarkResult
-from ax.benchmark.problems.surrogate import SurrogateBenchmarkProblem
 from ax.benchmark.runners.botorch_test import (
     ParamBasedTestProblem,
     ParamBasedTestProblemRunner,
 )
-from ax.benchmark.runners.surrogate import SurrogateRunner, SurrogateTestFunction
+from ax.benchmark.runners.surrogate import SurrogateTestFunction
 from ax.core.experiment import Experiment
 from ax.core.objective import MultiObjective, Objective
 from ax.core.optimization_config import (
@@ -129,41 +128,7 @@ def get_soo_surrogate() -> BenchmarkProblem:
     )
 
 
-def get_soo_surrogate_legacy() -> SurrogateBenchmarkProblem:
-    experiment = get_branin_experiment(with_completed_trial=True)
-    surrogate = TorchModelBridge(
-        experiment=experiment,
-        search_space=experiment.search_space,
-        model=BoTorchModel(surrogate=Surrogate(botorch_model_class=SingleTaskGP)),
-        data=experiment.lookup_data(),
-        transforms=[],
-    )
-    runner = SurrogateRunner(
-        name="test",
-        outcome_names=["branin"],
-        get_surrogate_and_datasets=lambda: (surrogate, []),
-    )
-
-    observe_noise_sd = True
-    objective = Objective(
-        metric=BenchmarkMetric(
-            name="branin", lower_is_better=True, observe_noise_sd=observe_noise_sd
-        ),
-    )
-    optimization_config = OptimizationConfig(objective=objective)
-
-    return SurrogateBenchmarkProblem(
-        name="test",
-        search_space=experiment.search_space,
-        optimization_config=optimization_config,
-        num_trials=6,
-        observe_noise_stds=observe_noise_sd,
-        optimal_value=0.0,
-        runner=runner,
-    )
-
-
-def get_moo_surrogate() -> SurrogateBenchmarkProblem:
+def get_moo_surrogate() -> BenchmarkProblem:
     experiment = get_branin_experiment_with_multi_objective(with_completed_trial=True)
     surrogate = TorchModelBridge(
         experiment=experiment,
@@ -173,11 +138,15 @@ def get_moo_surrogate() -> SurrogateBenchmarkProblem:
         transforms=[],
     )
 
-    runner = SurrogateRunner(
+    outcome_names = ["branin_a", "branin_b"]
+    test_function = SurrogateTestFunction(
         name="test",
-        outcome_names=["branin_a", "branin_b"],
+        outcome_names=outcome_names,
         get_surrogate_and_datasets=lambda: (surrogate, []),
     )
+    runner = ParamBasedTestProblemRunner(
+        test_problem=test_function, outcome_names=outcome_names
+    )
     observe_noise_sd = True
     optimization_config = MultiObjectiveOptimizationConfig(
         objective=MultiObjective(
@@ -199,7 +168,7 @@ def get_moo_surrogate() -> SurrogateBenchmarkProblem:
             ],
         )
     )
-    return SurrogateBenchmarkProblem(
+    return BenchmarkProblem(
         name="test",
         search_space=experiment.search_space,
         optimization_config=optimization_config,