diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala
index 933a5f1d52ed9..ae336982092d6 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala
@@ -745,12 +745,12 @@ class DistributedLDAModel private[clustering] (
           val N_wk = vertex._2
           val smoothed_N_wk: TopicCounts = N_wk + (eta - 1.0)
           val phi_wk: TopicCounts = smoothed_N_wk :/ smoothed_N_k
-          (eta - 1.0) * sum(phi_wk.map(math.log))
+          sumPrior + (eta - 1.0) * sum(phi_wk.map(math.log))
         } else {
           val N_kj = vertex._2
           val smoothed_N_kj: TopicCounts = N_kj + (alpha - 1.0)
           val theta_kj: TopicCounts = normalize(smoothed_N_kj, 1.0)
-          (alpha - 1.0) * sum(theta_kj.map(math.log))
+          sumPrior + (alpha - 1.0) * sum(theta_kj.map(math.log))
         }
     }
     graph.vertices.aggregate(0.0)(seqOp, _ + _)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala b/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala
index 3f39deddf20b4..9aa11fbdbe868 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala
@@ -260,6 +260,14 @@ class LDASuite extends SparkFunSuite with MLlibTestSparkContext with DefaultRead
         Vectors.dense(model2.topicsMatrix.toArray) absTol 1e-6)
       assert(Vectors.dense(model.getDocConcentration) ~==
         Vectors.dense(model2.getDocConcentration) absTol 1e-6)
+      val logPrior = model.asInstanceOf[DistributedLDAModel].logPrior
+      val logPrior2 = model2.asInstanceOf[DistributedLDAModel].logPrior
+      val trainingLogLikelihood =
+        model.asInstanceOf[DistributedLDAModel].trainingLogLikelihood
+      val trainingLogLikelihood2 =
+        model2.asInstanceOf[DistributedLDAModel].trainingLogLikelihood
+      assert(logPrior ~== logPrior2 absTol 1e-6)
+      assert(trainingLogLikelihood ~== trainingLogLikelihood2 absTol 1e-6)
     }
     val lda = new LDA()
     testEstimatorAndModelReadWrite(lda, dataset,