diff --git a/protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantRecalibrator.java b/protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantRecalibrator.java
index 9ed65b87d..f305c780b 100644
--- a/protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantRecalibrator.java
+++ b/protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantRecalibrator.java
@@ -319,6 +319,8 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
     private PrintStream tranchesStream;
     private final Set<String> ignoreInputFilterSet = new TreeSet<>();
     private final VariantRecalibratorEngine engine = new VariantRecalibratorEngine( VRAC );
+    private GaussianMixtureModel goodModel = null;
+    private GaussianMixtureModel badModel = null;
 
     //---------------------------------------------------------------------------------------------------------------
     //
@@ -356,7 +358,28 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
             throw new UserException.CommandLineException( "No truth set found! Please provide sets of known polymorphic loci marked with the truth=true ROD binding tag. For example, -resource:hapmap,VCF,known=false,training=true,truth=true,prior=12.0 hapmapFile.vcf" );
         }
 
-        final Set<VCFHeaderLine> hInfo = new HashSet<>();
+        final File inputFile = new File(inputModel);
+        if (inputFile.exists()) { // Load GMM from a file
+            logger.info("Loading model from:" + inputModel);
+            final GATKReport reportIn = new GATKReport(inputFile);
+
+            // Read all the tables
+            final GATKReportTable nmcTable = reportIn.getTable("NegativeModelCovariances");
+            final GATKReportTable nmmTable = reportIn.getTable("NegativeModelMeans");
+            final GATKReportTable nPMixTable = reportIn.getTable("BadGaussianPMix");
+            final GATKReportTable pmcTable = reportIn.getTable("PositiveModelCovariances");
+            final GATKReportTable pmmTable = reportIn.getTable("PositiveModelMeans");
+            final GATKReportTable pPMixTable = reportIn.getTable("GoodGaussianPMix");
+            final int numAnnotations = dataManager.getMeanVector().length;
+
+            goodModel = GMMFromTables(pmmTable, pmcTable, pPMixTable, numAnnotations);
+            badModel = GMMFromTables(nmmTable, nmcTable, nPMixTable, numAnnotations);
+        }
+
+
+
+
+            final Set<VCFHeaderLine> hInfo = new HashSet<>();
         ApplyRecalibration.addVQSRStandardHeaderLines(hInfo);
         recalWriter.writeHeader( new VCFHeader(hInfo) );
 
@@ -490,29 +513,14 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
                 dataManager.setData(reduceSum);
                 dataManager.normalizeData(); // Each data point is now (x - mean) / standard deviation
 
-                final GaussianMixtureModel goodModel, badModel;
+                //final GaussianMixtureModel goodModel, badModel;
                 final List<VariantDatum> positiveTrainingData = dataManager.getTrainingData();
                 final List<VariantDatum> negativeTrainingData;
 
-                final File inputFile = new File(inputModel);
-                if (inputFile.exists()){ // Load GMM from a file
-                    logger.info("Loading model from:"+inputModel);
-                    final GATKReport reportIn = new GATKReport(inputFile);
-
-                    // Read all the tables
-                    final GATKReportTable nmcTable = reportIn.getTable("NegativeModelCovariances");
-                    final GATKReportTable nmmTable = reportIn.getTable("NegativeModelMeans");
-                    final GATKReportTable nPMixTable = reportIn.getTable("BadGaussianPMix");
-                    final GATKReportTable pmcTable = reportIn.getTable("PositiveModelCovariances");
-                    final GATKReportTable pmmTable = reportIn.getTable("PositiveModelMeans");
-                    final GATKReportTable pPMixTable = reportIn.getTable("GoodGaussianPMix");
-                    final int numAnnotations = dataManager.getMeanVector().length;
-
-                    goodModel = GMMFromTables(pmmTable, pmcTable, pPMixTable, numAnnotations);
+                if (goodModel != null && badModel != null){ // GMMs were loaded from a file
+                    // Keeping this to maintain reproducibility between runs with and without serialized GMMs
                     engine.evaluateData(dataManager.getData(), goodModel, false);
                     negativeTrainingData = dataManager.selectWorstVariants();
-                    badModel = GMMFromTables(nmmTable, nmcTable, nPMixTable, numAnnotations);
-
                 } else { // Generate the GMMs from scratch
                     // Generate the positive model using the training data and evaluate each variant
                     goodModel = engine.generateModel(positiveTrainingData, VRAC.MAX_GAUSSIANS);
@@ -586,14 +594,13 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
 
         int curAnnotation = 0;
         for (GATKReportColumn reportColumn : muTable.getColumnInfo() ) {
-            logger.info("Report column name is:" + reportColumn.getColumnName());
             if (!reportColumn.getColumnName().equals("Gaussian")) {
                 for (int row = 0; row < muTable.getNumRows(); row++) {
                     if (gaussianList.size() <= row){
                         MultivariateGaussian mg = new MultivariateGaussian(numAnnotations);
                         gaussianList.add(mg);
                     }
-                    gaussianList.get(row).mu[curAnnotation] = reportObjectToDouble(muTable.get(row, reportColumn.getColumnName()));
+                    gaussianList.get(row).mu[curAnnotation] =  Double.parseDouble( (String)muTable.get(row, reportColumn.getColumnName()));
                 }
                 curAnnotation++;
             }
@@ -602,7 +609,7 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
         for (GATKReportColumn reportColumn : pmixTable.getColumnInfo() ) {
             if (reportColumn.getColumnName().equals("pMixLog10")) {
                 for (int row = 0; row < pmixTable.getNumRows(); row++) {
-                    gaussianList.get(row).pMixtureLog10 = reportObjectToDouble(pmixTable.get(row, reportColumn.getColumnName()));
+                    gaussianList.get(row).pMixtureLog10 =  Double.parseDouble( (String)pmixTable.get(row, reportColumn.getColumnName()));
                 }
             }
         }
@@ -615,7 +622,7 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
             for (int row = 0; row < sigmaTable.getNumRows(); row++) {
                 int curGaussian = row / numAnnotations;
                 int curI = row % numAnnotations;
-                double curVal =  reportObjectToDouble(sigmaTable.get(row, reportColumn.getColumnName()));
+                double curVal = Double.parseDouble( (String)sigmaTable.get(row, reportColumn.getColumnName()));
                 gaussianList.get(curGaussian).sigma.set(curI, curJ, curVal);
 
             }
@@ -627,14 +634,6 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
 
     }
 
-    private double reportObjectToDouble(Object obj){
-        if (obj instanceof String){
-            return Double.parseDouble((String)obj);
-        } else {
-            return (Double) obj;
-        }
-    }
-
     private double[] getStandardDeviationsFromTable(GATKReportTable astdTable){
         double[] stdVector = {};
 
@@ -642,7 +641,7 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
             if (reportColumn.getColumnName().equals("Standarddeviation")) {
                 stdVector = new double[astdTable.getNumRows()];
                 for (int row = 0; row < astdTable.getNumRows(); row++) {
-                    stdVector[row] =  reportObjectToDouble(astdTable.get(row, reportColumn.getColumnName()));
+                    stdVector[row] =  Double.parseDouble( (String)astdTable.get(row, reportColumn.getColumnName()));
                 }
             }
         }
@@ -657,7 +656,7 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
             if (reportColumn.getColumnName().equals("Mean")) {
                 meanVector = new double[amTable.getNumRows()];
                 for (int row = 0; row < amTable.getNumRows(); row++) {
-                    meanVector[row] =  reportObjectToDouble(amTable.get(row, reportColumn.getColumnName()));
+                    meanVector[row] =   Double.parseDouble( (String)amTable.get(row, reportColumn.getColumnName()));
                 }
             }
         }
@@ -666,7 +665,7 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
     }
 
     protected GATKReport writeModelReport(final GaussianMixtureModel goodModel, final GaussianMixtureModel badModel, List<String> annotationList) {
-        final String formatString = "%.25f";
+        final String formatString = "%.8f";
         final GATKReport report = new GATKReport();
 
         if (dataManager != null) {  //for unit test