diff --git a/h2o-core/src/main/java/hex/ModelBuilder.java b/h2o-core/src/main/java/hex/ModelBuilder.java
index ea55402c0ef0..b0b7a2567b5d 100644
--- a/h2o-core/src/main/java/hex/ModelBuilder.java
+++ b/h2o-core/src/main/java/hex/ModelBuilder.java
@@ -21,12 +21,6 @@
  */
 abstract public class ModelBuilder<M extends Model<M,P,O>, P extends Model.Parameters, O extends Model.Output> extends Iced {
 
-  private ModelBuilderListener _modelBuilderListener;
-
-  public void setModelBuilderListener(final ModelBuilderListener modelBuilderListener) {
-    this._modelBuilderListener = modelBuilderListener;
-  }
-
   public ToEigenVec getToEigenVec() { return null; }
   public boolean shouldReorder(Vec v) { return _parms._categorical_encoding.needsResponse() && isSupervised(); }
 
@@ -231,6 +225,13 @@ abstract protected class Driver extends H2O.H2OCountedCompleter<Driver> {
 
     protected Driver(){ super(); }
     protected Driver(H2O.H2OCountedCompleter completer){ super(completer); }
+    
+    private ModelBuilderListener _callback;
+
+    public void setCallback(ModelBuilderListener callback) {
+      this._callback = callback;
+    }
+
     // Pull the boilerplate out of the computeImpl(), so the algo writer doesn't need to worry about the following:
     // 1) Scope (unless they want to keep data, then they must call Scope.untrack(Key<Vec>[]))
     // 2) Train/Valid frame locking and unlocking
@@ -253,16 +254,16 @@ public void compute2() {
     @Override
     public void onCompletion(CountedCompleter caller) {
       setFinalState();
-      if (_modelBuilderListener != null) {
-        _modelBuilderListener.onModelSuccess(_result.get());
+      if (_callback != null) {
+        _callback.onModelSuccess(_result.get());
       }
     }
 
     @Override
     public boolean onExceptionalCompletion(Throwable ex, CountedCompleter caller) {
       setFinalState();
-      if (_modelBuilderListener != null) {
-        _modelBuilderListener.onModelFailure(ex, _parms);
+      if (_callback != null) {
+        _callback.onModelFailure(ex, _parms);
       }
       return true;
     }
@@ -287,7 +288,6 @@ private void setFinalState() {
     if (res != null && res._output != null) {
       res._output._job = _job;
       res._output.stopClock();
-//      res.unlock(_job == null ? null : _job._key, false); // last resort: dirty way to force unlock to be able to reacquire lock
       res.write_lock(_job);
       res.update(_job);
       res.unlock(_job);
@@ -357,31 +357,45 @@ public void run() {
 
   /** Method to launch training of a Model, based on its parameters. */
   final public Job<M> trainModel() {
+    return trainModel(null);
+  }
+
+  final public Job<M> trainModel(final ModelBuilderListener callback) {
     if (error_count() > 0)
       throw H2OModelBuilderIllegalArgumentException.makeFromBuilder(this);
     startClock();
-    if( !nFoldCV() )
-      return _job.start(trainModelImpl(), _parms.progressUnits(), _parms._max_runtime_secs);
-
-    // cross-validation needs to be forked off to allow continuous (non-blocking) progress bar
-    return _job.start(new H2O.H2OCountedCompleter() {
-                        @Override
-                        public void compute2() {
-                          computeCrossValidation();
-                          tryComplete();
-                        }
-                        @Override
-                        public boolean onExceptionalCompletion(Throwable ex, CountedCompleter caller) {
-                          Log.warn("Model training job "+_job._description+" completed with exception: "+ex);
-                          try {
-                            Keyed.remove(_job._result); //ensure there's no incomplete model left for manipulation after crash or cancellation
-                          } catch (Exception logged) {
-                            Log.warn("Exception thrown when removing result from job "+ _job._description, logged);
+    if (!nFoldCV()) {
+      Driver driver = trainModelImpl();
+      driver.setCallback(callback);
+      return _job.start(driver, _parms.progressUnits(), _parms._max_runtime_secs);
+    } else {
+      // cross-validation needs to be forked off to allow continuous (non-blocking) progress bar
+      return _job.start(new H2O.H2OCountedCompleter() {
+                          @Override
+                          public void compute2() {
+                            computeCrossValidation();
+                            tryComplete();
+                          }
+
+                          @Override
+                          public void onCompletion(CountedCompleter caller) {
+                            if (callback != null) callback.onModelSuccess(_result.get());
                           }
-                          return true;
-                        }
-                      },
-            (nFoldWork()+1/*main model*/) * _parms.progressUnits(), _parms._max_runtime_secs);
+
+                          @Override
+                          public boolean onExceptionalCompletion(Throwable ex, CountedCompleter caller) {
+                            Log.warn("Model training job " + _job._description + " completed with exception: " + ex);
+                            if (callback != null) callback.onModelFailure(ex, _parms);
+                            try {
+                              Keyed.remove(_job._result); // ensure there's no incomplete model left for manipulation after crash or cancellation
+                            } catch (Exception logged) {
+                              Log.warn("Exception thrown when removing result from job " + _job._description, logged);
+                            }
+                            return true;
+                          }
+                        },
+          (nFoldWork() + 1/*main model*/) * _parms.progressUnits(), _parms._max_runtime_secs);
+    }
   }
 
   /**
diff --git a/h2o-core/src/main/java/hex/ParallelModelBuilder.java b/h2o-core/src/main/java/hex/ParallelModelBuilder.java
index 9528d727a6e7..98bb175a165e 100644
--- a/h2o-core/src/main/java/hex/ParallelModelBuilder.java
+++ b/h2o-core/src/main/java/hex/ParallelModelBuilder.java
@@ -1,6 +1,7 @@
 package hex;
 
 import jsr166y.ForkJoinTask;
+import org.apache.log4j.Logger;
 import water.Iced;
 import water.util.IcedAtomicInt;
 
@@ -15,12 +16,15 @@
  * released the barrier inside.
  */
 public class ParallelModelBuilder extends ForkJoinTask<ParallelModelBuilder> {
+  
+  private static final Logger LOG = Logger.getLogger(ParallelModelBuilder.class);
 
   public static abstract class ParallelModelBuilderCallback<D extends ParallelModelBuilderCallback> extends Iced<D> {
 
     public abstract void onBuildSuccess(final Model model, final ParallelModelBuilder parallelModelBuilder);
 
     public abstract void onBuildFailure(final ModelBuildFailure modelBuildFailure, final ParallelModelBuilder parallelModelBuilder);
+
   }
 
   private final transient ParallelModelBuilderCallback _callback;
@@ -40,13 +44,11 @@ public ParallelModelBuilder(final ParallelModelBuilderCallback callback) {
    * @param modelBuilders An {@link Collection} of {@link ModelBuilder} to execute in parallel.
    */
   public void run(final Collection<ModelBuilder> modelBuilders) {
-      for (final ModelBuilder modelBuilder : modelBuilders) {
-        _modelInProgressCounter.incrementAndGet();
-
-        // Set the callbacks
-        modelBuilder.setModelBuilderListener(_parallelModelBuiltListener);
-        modelBuilder.trainModel();
-      }
+    if (LOG.isTraceEnabled()) LOG.trace("run with " + modelBuilders.size() + " models");
+    for (final ModelBuilder modelBuilder : modelBuilders) {
+      _modelInProgressCounter.incrementAndGet();
+      modelBuilder.trainModel(_parallelModelBuiltListener);
+    }
   }
 
 
@@ -54,25 +56,19 @@ private class ParallelModelBuiltListener extends ModelBuilderListener<ParallelMo
 
     @Override
     public void onModelSuccess(Model model) {
-      if (! model._parms._is_cv_model) {
-        try {
-          _callback.onBuildSuccess(model, ParallelModelBuilder.this);
-        } finally {
-          _modelInProgressCounter.decrementAndGet();
-        }
+      try {
+        _callback.onBuildSuccess(model, ParallelModelBuilder.this);
+      } finally {
         attemptComplete();
       }
     }
 
     @Override
     public void onModelFailure(Throwable cause, Model.Parameters parameters) {
-      if (! parameters._is_cv_model) {
-        try {
-          final ModelBuildFailure modelBuildFailure = new ModelBuildFailure(cause, parameters);
-          _callback.onBuildFailure(modelBuildFailure, ParallelModelBuilder.this);
-        } finally {
-          _modelInProgressCounter.decrementAndGet();
-        }
+      try {
+        final ModelBuildFailure modelBuildFailure = new ModelBuildFailure(cause, parameters);
+        _callback.onBuildFailure(modelBuildFailure, ParallelModelBuilder.this);
+      } finally {
         attemptComplete();
       }
     }
@@ -99,9 +95,12 @@ public Model.Parameters getParameters() {
     }
   }
   
-  private void attemptComplete(){
-    if(_modelInProgressCounter.get() != 0) return;
-    complete(this);
+  private void attemptComplete() {
+    int modelsInProgress = _modelInProgressCounter.decrementAndGet();
+    if (LOG.isTraceEnabled()) LOG.trace("Completed a model, left in progress: " + modelsInProgress);
+    if (modelsInProgress == 0) {
+      complete(this);
+    }
   }
 
 
diff --git a/h2o-py/tests/testdir_algos/grid/pyunit_grid_parallel_cv_error.py b/h2o-py/tests/testdir_algos/grid/pyunit_grid_parallel_cv_error.py
new file mode 100644
index 000000000000..79c5b6c66ca3
--- /dev/null
+++ b/h2o-py/tests/testdir_algos/grid/pyunit_grid_parallel_cv_error.py
@@ -0,0 +1,38 @@
+import sys
+import os
+import random
+
+sys.path.insert(1, os.path.join("..", "..", ".."))
+import h2o
+from tests import pyunit_utils
+from h2o.grid.grid_search import H2OGridSearch
+from h2o.estimators.gbm import H2OGradientBoostingEstimator
+
+
+def grid_parallel():
+    train = h2o.import_file(path=pyunit_utils.locate("smalldata/iris/iris_wheader.csv"))
+    fold_assignments = h2o.H2OFrame([[random.randint(0, 4)] for f in range(train.nrow)])
+    fold_assignments.set_names(["fold_assignment"])
+    train = train.cbind(fold_assignments)
+
+    hyper_parameters = {
+        "ntrees": [1, 3, 5],
+        "min_rows": [1, 10, 100]
+    }
+    print("GBM grid with the following hyper_parameters:", hyper_parameters)
+
+    gs = H2OGridSearch(
+        H2OGradientBoostingEstimator, 
+        hyper_params=hyper_parameters, 
+        parallelism=4
+    )
+    gs.train(x=list(range(4)), y=4, training_frame=train, fold_column="fold_assignment")
+    assert gs is not None
+    # only six models are trained, since CV is not possible with min_rows=100
+    assert len(gs.model_ids) == 6
+
+
+if __name__ == "__main__":
+    pyunit_utils.standalone_test(grid_parallel)
+else:
+    grid_parallel()