diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
index 180023922a9b0..127234036270d 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
@@ -17,12 +17,18 @@
 
 package org.apache.spark.mllib.clustering
 
-import org.apache.spark.{Logging, SparkException}
+import org.json4s._
+import org.json4s.JsonDSL._
+import org.json4s.jackson.JsonMethods._
+
+import org.apache.spark.sql.{Row, SQLContext}
+import org.apache.spark.{SparkContext, Logging, SparkException}
 import org.apache.spark.annotation.Experimental
 import org.apache.spark.api.java.JavaRDD
 import org.apache.spark.graphx._
 import org.apache.spark.graphx.impl.GraphImpl
 import org.apache.spark.mllib.linalg.Vectors
+import org.apache.spark.mllib.util.{Loader, Saveable}
 import org.apache.spark.mllib.util.MLUtils
 import org.apache.spark.rdd.RDD
 import org.apache.spark.util.random.XORShiftRandom
@@ -38,7 +44,63 @@ import org.apache.spark.util.random.XORShiftRandom
 @Experimental
 class PowerIterationClusteringModel(
     val k: Int,
-    val assignments: RDD[PowerIterationClustering.Assignment]) extends Serializable
+    val assignments: RDD[PowerIterationClustering.Assignment]) extends Saveable with Serializable {
+
+  override def save(sc: SparkContext, path: String): Unit = {
+    PowerIterationClusteringModel.SaveLoadV1_0.save(sc, this, path)
+  }
+
+  override protected def formatVersion: String = "1.0"
+}
+
+object PowerIterationClusteringModel extends Loader[PowerIterationClusteringModel] {
+  override def load(sc: SparkContext, path: String): PowerIterationClusteringModel = {
+    PowerIterationClusteringModel.SaveLoadV1_0.load(sc, path)
+  }
+
+  private[clustering]
+  object SaveLoadV1_0 {
+
+    private val thisFormatVersion = "1.0"
+
+    private[clustering]
+    val thisClassName = "org.apache.spark.mllib.clustering.PowerIterationClusteringModel"
+
+    def save(sc: SparkContext, model: PowerIterationClusteringModel, path: String): Unit = {
+      val sqlContext = new SQLContext(sc)
+      import sqlContext.implicits._
+
+      val metadata = compact(render(
+        ("class" -> thisClassName) ~ ("version" -> thisFormatVersion) ~ ("k" -> model.k)))
+      sc.parallelize(Seq(metadata), 1).saveAsTextFile(Loader.metadataPath(path))
+
+      val dataRDD = model.assignments.map(Tuple1.apply).toDF("assignment")
+      dataRDD.saveAsParquetFile(Loader.dataPath(path))
+    }
+
+    def load(sc: SparkContext, path: String): PowerIterationClusteringModel = {
+      implicit val formats = DefaultFormats
+      val sqlContext = new SQLContext(sc)
+
+      val (className, formatVersion, metadata) = Loader.loadMetadata(sc, path)
+      assert(className == thisClassName)
+      assert(formatVersion == thisFormatVersion)
+
+      val k = (metadata \ "k").extract[Int]
+      val assignments = sqlContext.parquetFile(Loader.dataPath(path))
+      Loader.checkSchema[Tuple1[PowerIterationClustering.Assignment]](assignments.schema)
+
+      val assignmentsRDD = assignments.map {
+        case Row(Tuple1(x: PowerIterationClustering.Assignment)) => x
+      }
+
+      val realK = assignmentsRDD.map(_.cluster).distinct().collect().size
+      assert(k == realK)
+
+      new PowerIterationClusteringModel(k, assignmentsRDD)
+    }
+  }
+}
 
 /**
  * :: Experimental ::