diff --git a/tests/benchmark-models/test_petab_model.py b/tests/benchmark-models/test_petab_model.py
index 64af79d8a8..89a482cd7a 100755
--- a/tests/benchmark-models/test_petab_model.py
+++ b/tests/benchmark-models/test_petab_model.py
@@ -145,65 +145,50 @@ def main():
     rdatas = res[RDATAS]
     llh = res[LLH]
 
-    if (
-        args.model_name
-        not in (
-            # "Beer_MolBioSystems2014",
-            # "Brannmark_JBC2010",
-            # "Fujita_SciSignal2010",
-            # "Isensee_JCB2018",
-            # "Smith_BMCSystBiol2013",
-            # "Weber_BMC2015",
-        )
-    ):
-        # Beer: Heaviside
-        # Brannmark: Heaviside
-        # Fujita: Heaviside
-        # Isensee: Heaviside
-        # Smith: Heaviside
-        # Weber: Heaviside
-
-        jax_model = model_module.get_jax_model()
-        simulation_conditions = (
-            problem.get_simulation_conditions_from_measurement_df()
-        )
-        edatas = create_edatas(
-            amici_model=amici_model,
-            petab_problem=problem,
-            simulation_conditions=simulation_conditions,
-        )
-        problem_parameters = {
-            t.Index: getattr(t, petab.NOMINAL_VALUE)
-            for t in problem.parameter_df.itertuples()
-        }
-        parameter_mapping = create_parameter_mapping(
-            petab_problem=problem,
-            simulation_conditions=simulation_conditions,
-            scaled_parameters=False,
-            amici_model=amici_model,
-        )
-        fill_in_parameters(
-            edatas=edatas,
-            problem_parameters=problem_parameters,
-            scaled_parameters=False,
-            parameter_mapping=parameter_mapping,
-            amici_model=amici_model,
-        )
-        # run once to JIT
-        jax_model.run_simulations(edatas)
-        start_jax = timer()
-        rdatas_jax = jax_model.run_simulations(edatas)
-        end_jax = timer()
+    jax_model = model_module.get_jax_model()
+    simulation_conditions = (
+        problem.get_simulation_conditions_from_measurement_df()
+    )
+    edatas = create_edatas(
+        amici_model=amici_model,
+        petab_problem=problem,
+        simulation_conditions=simulation_conditions,
+    )
+    problem_parameters = {
+        t.Index: getattr(t, petab.NOMINAL_VALUE)
+        for t in problem.parameter_df.itertuples()
+    }
+    parameter_mapping = create_parameter_mapping(
+        petab_problem=problem,
+        simulation_conditions=simulation_conditions,
+        scaled_parameters=False,
+        amici_model=amici_model,
+    )
+    fill_in_parameters(
+        edatas=edatas,
+        problem_parameters=problem_parameters,
+        scaled_parameters=False,
+        parameter_mapping=parameter_mapping,
+        amici_model=amici_model,
+    )
+    # run once to JIT
+    jax_model.run_simulations(edatas)
+    start_jax = timer()
+    rdatas_jax = jax_model.run_simulations(edatas)
+    end_jax = timer()
 
-        t_jax = end_jax - start_jax
-        t_amici = sum(r.cpu_time for r in rdatas) / 1e3
+    t_jax = end_jax - start_jax
+    t_amici = sum(r.cpu_time for r in rdatas) / 1e3
 
-        llh_jax = sum(r.llh for r in rdatas_jax)
+    llh_jax = sum(r.llh for r in rdatas_jax)
 
-        print(
-            f'amici (llh={res["llh"]} after {t_amici}s) vs '
-            f'jax (llh={llh_jax} after {t_jax}s)'
-        )
+    print(
+        f'amici (llh={res["llh"]} after {t_amici}s) vs '
+        f'jax (llh={llh_jax} after {t_jax}s)'
+    )
+    assert np.isclose(
+        llh, llh_jax, rtol=1e-3, atol=1e-3
+    ), "LLH mismatch {llh} (amici) vs {llh_jax} (jax)"
 
     times = dict()