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/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 6888a1efbaa..e5a467f9f0a 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(
+    test_function = SurrogateTestFunction(
+        num_objectives=2,
         name="test",
-        outcome_names=["branin_a", "branin_b"],
         get_surrogate_and_datasets=lambda: (surrogate, []),
     )
+    runner = ParamBasedTestProblemRunner(
+        test_problem=test_function,
+        outcome_names=["branin_a", "branin_b"],
+    )
     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,