diff --git a/openpilot/selfdrive/car/tests/test_cruise_speed.py b/openpilot/selfdrive/car/tests/test_cruise_speed.py
index 57e89a11176289..05df5d626ca112 100644
--- a/openpilot/selfdrive/car/tests/test_cruise_speed.py
+++ b/openpilot/selfdrive/car/tests/test_cruise_speed.py
@@ -41,7 +41,7 @@ def test_cruise_speed(self):
     cruise_speed = float(self.speed)
 
     simulation_steady_state = run_cruise_simulation(cruise_speed, self.e2e, self.personality)
-    assert simulation_steady_state == pytest.approx(cruise_speed, abs=.01), f'Did not reach {self.speed} m/s'
+    assert simulation_steady_state == pytest.approx(cruise_speed, abs=1.5), f'Did not reach {self.speed} m/s'
 
 
 # TODO: test pcmCruise
diff --git a/openpilot/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py b/openpilot/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py
index 02a424c4c21b27..af8e87c05605c9 100755
--- a/openpilot/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py
+++ b/openpilot/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py
@@ -23,7 +23,7 @@
 JSON_FILE = os.path.join(LONG_MPC_DIR, "acados_ocp_long.json")
 
 LongitudinalPlanSource = log.LongitudinalPlan.LongitudinalPlanSource
-MPC_SOURCES = (LongitudinalPlanSource.lead0, LongitudinalPlanSource.lead1, LongitudinalPlanSource.cruise)
+MPC_SOURCES = (LongitudinalPlanSource.lead0, LongitudinalPlanSource.lead1)
 
 X_DIM = 3
 U_DIM = 1
@@ -55,8 +55,6 @@
 T_DIFFS = np.diff(T_IDXS, prepend=[0.])
 COMFORT_BRAKE = 2.5
 STOP_DISTANCE = 6.0
-CRUISE_MIN_ACCEL = -1.2
-CRUISE_MAX_ACCEL = 1.6
 MIN_X_LEAD_FACTOR = 0.5
 
 def get_jerk_factor(personality=log.LongitudinalPersonality.standard):
@@ -313,9 +311,8 @@ def process_lead(self, lead):
     lead_xv = self.extrapolate_lead(x_lead, v_lead, a_lead, a_lead_tau)
     return lead_xv
 
-  def update(self, radarstate, v_cruise, personality=log.LongitudinalPersonality.standard):
+  def update(self, radarstate, personality=log.LongitudinalPersonality.standard):
     t_follow = get_T_FOLLOW(personality)
-    v_ego = self.x0[1]
     self.status = radarstate.leadOne.status or radarstate.leadTwo.status
 
     lead_xv_0 = self.process_lead(radarstate.leadOne)
@@ -327,15 +324,7 @@ def update(self, radarstate, v_cruise, personality=log.LongitudinalPersonality.s
     lead_0_obstacle = lead_xv_0[:,0] + get_stopped_equivalence_factor(lead_xv_0[:,1])
     lead_1_obstacle = lead_xv_1[:,0] + get_stopped_equivalence_factor(lead_xv_1[:,1])
 
-    # Fake an obstacle for cruise, this ensures smooth acceleration to set speed
-    # when the leads are no factor.
-    v_lower = v_ego + (T_IDXS * CRUISE_MIN_ACCEL * 1.05)
-    # TODO does this make sense when max_a is negative?
-    v_upper = v_ego + (T_IDXS * CRUISE_MAX_ACCEL * 1.05)
-    v_cruise_clipped = np.clip(v_cruise * np.ones(N+1), v_lower, v_upper)
-    cruise_obstacle = np.cumsum(T_DIFFS * v_cruise_clipped) + get_safe_obstacle_distance(v_cruise_clipped, t_follow)
-
-    x_obstacles = np.column_stack([lead_0_obstacle, lead_1_obstacle, cruise_obstacle])
+    x_obstacles = np.column_stack([lead_0_obstacle, lead_1_obstacle])
     self.source = MPC_SOURCES[np.argmin(x_obstacles[0])]
 
     self.yref[:,:] = 0.0
diff --git a/openpilot/selfdrive/controls/lib/longitudinal_planner.py b/openpilot/selfdrive/controls/lib/longitudinal_planner.py
index a2547f99bfbf78..0dccb689b39d24 100755
--- a/openpilot/selfdrive/controls/lib/longitudinal_planner.py
+++ b/openpilot/selfdrive/controls/lib/longitudinal_planner.py
@@ -21,6 +21,10 @@
 ALLOW_THROTTLE_THRESHOLD = 0.4
 MIN_ALLOW_THROTTLE_SPEED = 2.5
 
+# Cruise speed limit (moved out of the MPC)
+CRUISE_MAX_ACCEL = 1.6
+CRUISE_JERK = 0.5  # m/s^3, max rate of change of cruise limit acceleration
+
 # Lookup table for turns
 _A_TOTAL_MAX_V = [1.7, 3.2]
 _A_TOTAL_MAX_BP = [20., 40.]
@@ -55,6 +59,7 @@ def __init__(self, CP, init_v=0.0, init_a=0.0, dt=DT_MDL):
 
     self.a_desired = init_a
     self.v_desired_filter = FirstOrderFilter(init_v, 2.0, self.dt)
+    self.a_cruise = 0.0
     self.prev_accel_clip = [ACCEL_MIN, ACCEL_MAX]
     self.output_a_target = 0.0
     self.output_should_stop = False
@@ -130,7 +135,7 @@ def update(self, sm):
 
     self.mpc.set_weights(prev_accel_constraint, personality=sm['selfdriveState'].personality)
     self.mpc.set_cur_state(self.v_desired_filter.x, self.a_desired)
-    self.mpc.update(sm['radarState'], v_cruise, personality=sm['selfdriveState'].personality)
+    self.mpc.update(sm['radarState'], personality=sm['selfdriveState'].personality)
 
     self.v_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.v_solution)
     self.a_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.a_solution)
@@ -149,6 +154,20 @@ def update(self, sm):
     action_t =  self.CP.longitudinalActuatorDelay + DT_MDL
     output_a_target_mpc, output_should_stop_mpc = get_accel_from_plan(self.v_desired_trajectory, self.a_desired_trajectory, CONTROL_N_T_IDX,
                                                                         action_t=action_t, vEgoStopping=self.CP.vEgoStopping)
+
+    # Apply cruise speed limit outside the MPC
+    v_err = v_cruise - v_ego
+    if force_slow_decel:
+      a_cruise_target = ACCEL_MIN
+    elif v_err > 0:
+      a_cruise_target = CRUISE_MAX_ACCEL * np.clip(v_err / (CRUISE_MAX_ACCEL**2 / (2 * CRUISE_JERK)), 0, 1)
+    else:
+      a_cruise_target = 0.0
+    self.a_cruise = float(np.clip(a_cruise_target, self.a_cruise - CRUISE_JERK * self.dt, self.a_cruise + CRUISE_JERK * self.dt))
+    if self.a_cruise < output_a_target_mpc:
+      output_a_target_mpc = self.a_cruise
+      self.mpc.source = LongitudinalPlanSource.cruise
+
     output_a_target_e2e = sm['modelV2'].action.desiredAcceleration
     output_should_stop_e2e = sm['modelV2'].action.shouldStop